Untitled.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "import codecs\n",
    "from docx import *\n",
    "import docx2txt\n",
    "from PIL import Image\n",
    "from wand.image import Image as IMG\n",
    "import pytesseract\n",
    "import textract\n",
    "\n",
    "def get_string(name):\n",
    "    img=Image.open(name)\n",
    "    utf8_text = pytesseract.image_to_string(img)\n",
    "    utf8_text = str(utf8_text.encode('ascii', 'ignore'))\n",
    "    return utf8_text\n",
    "\n",
    "data_dir = os.path.join('Resumes')\n",
    "resume_count = 0\n",
    "resume_text = \"all_text1.txt\"\n",
    "if 1==0:\n",
    "    with codecs.open(resume_text,'w',encoding='utf_8') as resume_txt:\n",
    "        for filename in os.listdir(data_dir):\n",
    "            print(filename)\n",
    "\n",
    "            s = \"\"\n",
    "            if filename.endswith(\".docx\"):\n",
    "                location = str(os.path.join(data_dir,filename))\n",
    "                #document = Document(location)\n",
    "                #for paragraph in document.paragraphs:\n",
    "                #    s += str(paragraph.text.encode(errors='ignore'))\n",
    "                s = docx2txt.process(location)\n",
    "                resume_txt.write(s+'\\\\n'+'\\n')\n",
    "                resume_count += 1\n",
    "\n",
    "\n",
    "            elif filename.endswith(\".pdf\"):\n",
    "                utf8_text = \"\"\n",
    "\n",
    "                temp_doc = textract.process(os.path.join(data_dir,filename))\n",
    "                if len(temp_doc) < 50:\n",
    "                    img=IMG(filename=os.path.join(data_dir,filename),resolution=200)\n",
    "\n",
    "                    img.save(filename=os.path.join(data_dir,'temp','temp.jpg'))\n",
    "                    for files in os.listdir(os.path.join(data_dir,'temp')):\n",
    "                        utf8_text += get_string(os.path.join(data_dir,'temp',files))\n",
    "                    for files in os.listdir(os.path.join(data_dir,'temp')):\n",
    "                        os.remove(os.path.join(data_dir,'temp',files))\n",
    "                    temp_doc = utf8_text\n",
    "\n",
    "                if type(temp_doc)==str:\n",
    "                    resume_txt.write(temp_doc+'\\\\n'+'\\n')    \n",
    "                else:\n",
    "                    resume_txt.write(temp_doc.decode(\"utf-8\")+'\\\\n'+'\\n')    \n",
    "                resume_count +=1\n",
    "                \n",
    "print(resume_count)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jared/Parsing/parseVirt/lib/python3.5/site-packages/requests/__init__.py:80: RequestsDependencyWarning: urllib3 (1.21.1) or chardet (2.3.0) doesn't match a supported version!\n",
      "  RequestsDependencyWarning)\n"
     ]
    }
   ],
   "source": [
    "import spacy\n",
    "import pandas as pd\n",
    "import itertools as it\n",
    "\n",
    "nlp = spacy.load('en')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "• B.S. Physiology and Neurobiology\n",
      "\n"
     ]
    }
   ],
   "source": [
    "with codecs.open(resume_text,encoding=\"utf_8\") as f:\n",
    "    sample_res = list(it.islice(f,8,9))[0]\n",
    "    sample_res = sample_res.replace('\\\\n','\\n')\n",
    "print(sample_res)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "• B.S. Physiology and Neurobiology\n",
      "\n"
     ]
    }
   ],
   "source": [
    "parsed_res_sample = nlp(sample_res)\n",
    "print(parsed_res_sample)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Entity • - \n",
      "Entity B.S. - PERSON\n",
      "Entity Physiology - PERSON\n",
      "Entity and - \n",
      "Entity Neurobiology - \n",
      "Entity \n",
      " - \n"
     ]
    }
   ],
   "source": [
    "for num,entity in enumerate(parsed_res_sample):\n",
    "    print(\"Entity\",entity, '-',entity.ent_type_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>token_text</th>\n",
       "      <th>token_lemma</th>\n",
       "      <th>token_shape</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>•</td>\n",
       "      <td>•</td>\n",
       "      <td>•</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>B.S.</td>\n",
       "      <td>b.s.</td>\n",
       "      <td>X.X.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Physiology</td>\n",
       "      <td>physiology</td>\n",
       "      <td>Xxxxx</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>and</td>\n",
       "      <td>and</td>\n",
       "      <td>xxx</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Neurobiology</td>\n",
       "      <td>neurobiology</td>\n",
       "      <td>Xxxxx</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>\\n</td>\n",
       "      <td>\\n</td>\n",
       "      <td>\\n</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     token_text   token_lemma token_shape\n",
       "0             •             •           •\n",
       "1          B.S.          b.s.        X.X.\n",
       "2    Physiology    physiology       Xxxxx\n",
       "3           and           and         xxx\n",
       "4  Neurobiology  neurobiology       Xxxxx\n",
       "5            \\n            \\n          \\n"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "token_text = [token.orth_ for token in parsed_res_sample]\n",
    "token_lemma = [token.lemma_ for token in parsed_res_sample]\n",
    "token_shape = [token.shape_ for token in parsed_res_sample]\n",
    "d = list(zip(token_text,token_lemma,token_shape))\n",
    "pd.DataFrame(data =d,\\\n",
    "            columns=['token_text','token_lemma','token_shape'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from gensim.models import Phrases\n",
    "from gensim.models.word2vec import LineSentence\n",
    "\n",
    "def punct_space(token):\n",
    "    \"helper that elimates puncations and whitespace\"\n",
    "    return token.is_punct or token.is_space\n",
    "\n",
    "def line_review(filename):\n",
    "    \"read reviews from the file and un-escapes orignal line break\"\n",
    "    with codecs.open(filename,encoding='utf_8') as f:\n",
    "        for res in f:\n",
    "            yield res.replace('\\\\n','\\n')\n",
    " \n",
    "def lemmatized_sentence_corpus(filename):\n",
    "    \"use spacy to parse, lemmatize and yield sentences\"\n",
    "    for parsed_res in nlp.pipe(line_review(filename),batch_size=10000,n_threads=3):\n",
    "        for sent in parsed_res.sents:\n",
    "            yield u' '.join([token.lemma_ for token in sent if not punct_space(token)])\n",
    "            \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "unigram_filepath = 'unigram_sentences.txt'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "with codecs.open(unigram_filepath,'w',encoding='utf_8') as f:\n",
    "    for sent in lemmatized_sentence_corpus(resume_text):\n",
    "        f.write(sent+'\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jared/Parsing/parseVirt/lib/python3.5/site-packages/gensim/models/phrases.py:274: UserWarning: For a faster implementation, use the gensim.models.phrases.Phraser class\n",
      "  warnings.warn(\"For a faster implementation, use the gensim.models.phrases.Phraser class\")\n"
     ]
    }
   ],
   "source": [
    "normal_res = LineSentence(unigram_filepath)\n",
    "bigram_sentence = ''\n",
    "normal_res2 = Phrases(normal_res)\n",
    "with codecs.open('bigram.txt', 'w', encoding='utf_8') as f:\n",
    "    for unigram_sentence in normal_res:        \n",
    "        bigram_sentence =  ' '.join(normal_res2[unigram_sentence])\n",
    "        f.write(bigram_sentence+'\\n')\n",
    "        \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jared/Parsing/parseVirt/lib/python3.5/site-packages/gensim/models/phrases.py:274: UserWarning: For a faster implementation, use the gensim.models.phrases.Phraser class\n",
      "  warnings.warn(\"For a faster implementation, use the gensim.models.phrases.Phraser class\")\n"
     ]
    }
   ],
   "source": [
    "bigram_sentences = LineSentence('bigram.txt')\n",
    "\n",
    "trigram_model = Phrases(bigram_sentences)\n",
    "with codecs.open('trigram.txt', 'w', encoding='utf_8') as f:\n",
    "    for unigram_sentence in bigram_sentences:        \n",
    "        trigram_sentence =  ' '.join(trigram_model[unigram_sentence])\n",
    "        f.write(trigram_sentence+'\\n')\n",
    "        \n",
    "normal_res1 = LineSentence('trigram.txt')\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from gensim.models import Word2Vec\n",
    "word2vec_file = \"vector_models\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "res2vec = Word2Vec(normal_res,size=300,window=10,sg=1,workers=4)\n",
    "res2vec.save(word2vec_file)\n",
    "\n",
    "for i in range(1,15):\n",
    "    res2vec.train(normal_res,total_examples=res2vec.corpus_count, epochs=res2vec.iter)\n",
    "    res2vec.save(word2vec_file)\n",
    "    \n",
    "res2vec = Word2Vec.load(word2vec_file)\n",
    "res2vec.init_sims()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
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       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
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       "      <th>9</th>\n",
       "      <th>...</th>\n",
       "      <th>290</th>\n",
       "      <th>291</th>\n",
       "      <th>292</th>\n",
       "      <th>293</th>\n",
       "      <th>294</th>\n",
       "      <th>295</th>\n",
       "      <th>296</th>\n",
       "      <th>297</th>\n",
       "      <th>298</th>\n",
       "      <th>299</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1200</th>\n",
       "      <td>-0.638761</td>\n",
       "      <td>-1.032748</td>\n",
       "      <td>-0.235092</td>\n",
       "      <td>-0.424974</td>\n",
       "      <td>-0.232226</td>\n",
       "      <td>0.822992</td>\n",
       "      <td>0.378264</td>\n",
       "      <td>0.139240</td>\n",
       "      <td>0.270665</td>\n",
       "      <td>-0.454389</td>\n",
       "      <td>...</td>\n",
       "      <td>0.111120</td>\n",
       "      <td>0.414765</td>\n",
       "      <td>0.284807</td>\n",
       "      <td>-0.556309</td>\n",
       "      <td>0.560266</td>\n",
       "      <td>0.236525</td>\n",
       "      <td>-0.376341</td>\n",
       "      <td>0.360399</td>\n",
       "      <td>-0.321175</td>\n",
       "      <td>-0.211022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cert</th>\n",
       "      <td>1.062055</td>\n",
       "      <td>-0.377882</td>\n",
       "      <td>0.104729</td>\n",
       "      <td>0.463845</td>\n",
       "      <td>0.262584</td>\n",
       "      <td>-0.365065</td>\n",
       "      <td>-0.061737</td>\n",
       "      <td>-0.226790</td>\n",
       "      <td>0.623428</td>\n",
       "      <td>-0.030326</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.319437</td>\n",
       "      <td>-0.404249</td>\n",
       "      <td>0.319670</td>\n",
       "      <td>-0.123425</td>\n",
       "      <td>0.190857</td>\n",
       "      <td>0.158566</td>\n",
       "      <td>0.025808</td>\n",
       "      <td>-0.487723</td>\n",
       "      <td>-0.201767</td>\n",
       "      <td>0.013518</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>related</th>\n",
       "      <td>-0.004273</td>\n",
       "      <td>-0.443045</td>\n",
       "      <td>0.640763</td>\n",
       "      <td>-0.345597</td>\n",
       "      <td>0.122523</td>\n",
       "      <td>0.576840</td>\n",
       "      <td>-0.175022</td>\n",
       "      <td>0.299697</td>\n",
       "      <td>0.165816</td>\n",
       "      <td>-0.234568</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.099955</td>\n",
       "      <td>-0.034384</td>\n",
       "      <td>-0.077073</td>\n",
       "      <td>-0.117772</td>\n",
       "      <td>0.584124</td>\n",
       "      <td>0.348149</td>\n",
       "      <td>0.085304</td>\n",
       "      <td>0.215114</td>\n",
       "      <td>0.599803</td>\n",
       "      <td>0.631225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>artificial</th>\n",
       "      <td>-0.381334</td>\n",
       "      <td>-0.306404</td>\n",
       "      <td>0.648571</td>\n",
       "      <td>-0.126388</td>\n",
       "      <td>-0.123929</td>\n",
       "      <td>0.320392</td>\n",
       "      <td>0.162330</td>\n",
       "      <td>-0.216915</td>\n",
       "      <td>0.485710</td>\n",
       "      <td>-0.072828</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.508576</td>\n",
       "      <td>0.065971</td>\n",
       "      <td>0.300530</td>\n",
       "      <td>0.151014</td>\n",
       "      <td>-0.175000</td>\n",
       "      <td>-0.197794</td>\n",
       "      <td>0.076596</td>\n",
       "      <td>-0.275751</td>\n",
       "      <td>0.313868</td>\n",
       "      <td>-0.356102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>calculus</th>\n",
       "      <td>-0.247304</td>\n",
       "      <td>-0.327844</td>\n",
       "      <td>-0.156382</td>\n",
       "      <td>-0.447890</td>\n",
       "      <td>0.376691</td>\n",
       "      <td>0.275214</td>\n",
       "      <td>0.127010</td>\n",
       "      <td>0.901065</td>\n",
       "      <td>0.539872</td>\n",
       "      <td>-0.773755</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.041095</td>\n",
       "      <td>-0.453284</td>\n",
       "      <td>0.199223</td>\n",
       "      <td>-0.029136</td>\n",
       "      <td>0.237765</td>\n",
       "      <td>0.179573</td>\n",
       "      <td>0.189013</td>\n",
       "      <td>0.561403</td>\n",
       "      <td>-0.283585</td>\n",
       "      <td>-0.057771</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 300 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 0         1         2         3         4         5    \\\n",
       "1200       -0.638761 -1.032748 -0.235092 -0.424974 -0.232226  0.822992   \n",
       "cert        1.062055 -0.377882  0.104729  0.463845  0.262584 -0.365065   \n",
       "related    -0.004273 -0.443045  0.640763 -0.345597  0.122523  0.576840   \n",
       "artificial -0.381334 -0.306404  0.648571 -0.126388 -0.123929  0.320392   \n",
       "calculus   -0.247304 -0.327844 -0.156382 -0.447890  0.376691  0.275214   \n",
       "\n",
       "                 6         7         8         9      ...          290  \\\n",
       "1200        0.378264  0.139240  0.270665 -0.454389    ...     0.111120   \n",
       "cert       -0.061737 -0.226790  0.623428 -0.030326    ...    -0.319437   \n",
       "related    -0.175022  0.299697  0.165816 -0.234568    ...    -0.099955   \n",
       "artificial  0.162330 -0.216915  0.485710 -0.072828    ...    -0.508576   \n",
       "calculus    0.127010  0.901065  0.539872 -0.773755    ...    -0.041095   \n",
       "\n",
       "                 291       292       293       294       295       296  \\\n",
       "1200        0.414765  0.284807 -0.556309  0.560266  0.236525 -0.376341   \n",
       "cert       -0.404249  0.319670 -0.123425  0.190857  0.158566  0.025808   \n",
       "related    -0.034384 -0.077073 -0.117772  0.584124  0.348149  0.085304   \n",
       "artificial  0.065971  0.300530  0.151014 -0.175000 -0.197794  0.076596   \n",
       "calculus   -0.453284  0.199223 -0.029136  0.237765  0.179573  0.189013   \n",
       "\n",
       "                 297       298       299  \n",
       "1200        0.360399 -0.321175 -0.211022  \n",
       "cert       -0.487723 -0.201767  0.013518  \n",
       "related     0.215114  0.599803  0.631225  \n",
       "artificial -0.275751  0.313868 -0.356102  \n",
       "calculus    0.561403 -0.283585 -0.057771  \n",
       "\n",
       "[5 rows x 300 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ordered = [(term,voc.index,voc.count)for term, voc in res2vec.wv.vocab.items()]\n",
    "ordered_terms,term_indices,term_count = zip(*ordered)\n",
    "word_vectors = pd.DataFrame(res2vec.wv.syn0[term_indices,:],index=ordered_terms)\n",
    "\n",
    "word_vectors.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.25366593502438511"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res2vec.n_similarity(['python'],['java'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def get_related_terms(token,topn=10):\n",
    "    \"get the top n most similar terms\"\n",
    "    for word,similar in res2vec.wv.most_similar(positive = [token],topn=topn):\n",
    "        print(word,':',round(similar,3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3-sectored : 0.423\n",
      "bash : 0.409\n",
      "verilog : 0.403\n",
      "html5 : 0.386\n",
      "languag : 0.384\n",
      "ocaml : 0.379\n",
      "perl : 0.375\n",
      "languages : 0.371\n",
      "impala : 0.365\n",
      "sqoop : 0.361\n"
     ]
    }
   ],
   "source": [
    "get_related_terms('python')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "j2me : 0.499\n",
      "j2ee : 0.46\n",
      "j2se : 0.449\n",
      "swings : 0.446\n",
      "jsp : 0.439\n",
      "rmi : 0.419\n",
      "taglibs : 0.413\n",
      "1.6 : 0.405\n",
      "applets : 0.405\n",
      "javascript : 0.402\n"
     ]
    }
   ],
   "source": [
    "get_related_terms('java')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
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       "      <th>291</th>\n",
       "      <th>292</th>\n",
       "      <th>293</th>\n",
       "      <th>294</th>\n",
       "      <th>295</th>\n",
       "      <th>296</th>\n",
       "      <th>297</th>\n",
       "      <th>298</th>\n",
       "      <th>299</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1200</th>\n",
       "      <td>-0.638761</td>\n",
       "      <td>-1.032748</td>\n",
       "      <td>-0.235092</td>\n",
       "      <td>-0.424974</td>\n",
       "      <td>-0.232226</td>\n",
       "      <td>0.822992</td>\n",
       "      <td>0.378264</td>\n",
       "      <td>0.139240</td>\n",
       "      <td>0.270665</td>\n",
       "      <td>-0.454389</td>\n",
       "      <td>...</td>\n",
       "      <td>0.111120</td>\n",
       "      <td>0.414765</td>\n",
       "      <td>0.284807</td>\n",
       "      <td>-0.556309</td>\n",
       "      <td>0.560266</td>\n",
       "      <td>0.236525</td>\n",
       "      <td>-0.376341</td>\n",
       "      <td>0.360399</td>\n",
       "      <td>-0.321175</td>\n",
       "      <td>-0.211022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cert</th>\n",
       "      <td>1.062055</td>\n",
       "      <td>-0.377882</td>\n",
       "      <td>0.104729</td>\n",
       "      <td>0.463845</td>\n",
       "      <td>0.262584</td>\n",
       "      <td>-0.365065</td>\n",
       "      <td>-0.061737</td>\n",
       "      <td>-0.226790</td>\n",
       "      <td>0.623428</td>\n",
       "      <td>-0.030326</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.319437</td>\n",
       "      <td>-0.404249</td>\n",
       "      <td>0.319670</td>\n",
       "      <td>-0.123425</td>\n",
       "      <td>0.190857</td>\n",
       "      <td>0.158566</td>\n",
       "      <td>0.025808</td>\n",
       "      <td>-0.487723</td>\n",
       "      <td>-0.201767</td>\n",
       "      <td>0.013518</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>related</th>\n",
       "      <td>-0.004273</td>\n",
       "      <td>-0.443045</td>\n",
       "      <td>0.640763</td>\n",
       "      <td>-0.345597</td>\n",
       "      <td>0.122523</td>\n",
       "      <td>0.576840</td>\n",
       "      <td>-0.175022</td>\n",
       "      <td>0.299697</td>\n",
       "      <td>0.165816</td>\n",
       "      <td>-0.234568</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.099955</td>\n",
       "      <td>-0.034384</td>\n",
       "      <td>-0.077073</td>\n",
       "      <td>-0.117772</td>\n",
       "      <td>0.584124</td>\n",
       "      <td>0.348149</td>\n",
       "      <td>0.085304</td>\n",
       "      <td>0.215114</td>\n",
       "      <td>0.599803</td>\n",
       "      <td>0.631225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>artificial</th>\n",
       "      <td>-0.381334</td>\n",
       "      <td>-0.306404</td>\n",
       "      <td>0.648571</td>\n",
       "      <td>-0.126388</td>\n",
       "      <td>-0.123929</td>\n",
       "      <td>0.320392</td>\n",
       "      <td>0.162330</td>\n",
       "      <td>-0.216915</td>\n",
       "      <td>0.485710</td>\n",
       "      <td>-0.072828</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.508576</td>\n",
       "      <td>0.065971</td>\n",
       "      <td>0.300530</td>\n",
       "      <td>0.151014</td>\n",
       "      <td>-0.175000</td>\n",
       "      <td>-0.197794</td>\n",
       "      <td>0.076596</td>\n",
       "      <td>-0.275751</td>\n",
       "      <td>0.313868</td>\n",
       "      <td>-0.356102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>calculus</th>\n",
       "      <td>-0.247304</td>\n",
       "      <td>-0.327844</td>\n",
       "      <td>-0.156382</td>\n",
       "      <td>-0.447890</td>\n",
       "      <td>0.376691</td>\n",
       "      <td>0.275214</td>\n",
       "      <td>0.127010</td>\n",
       "      <td>0.901065</td>\n",
       "      <td>0.539872</td>\n",
       "      <td>-0.773755</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.041095</td>\n",
       "      <td>-0.453284</td>\n",
       "      <td>0.199223</td>\n",
       "      <td>-0.029136</td>\n",
       "      <td>0.237765</td>\n",
       "      <td>0.179573</td>\n",
       "      <td>0.189013</td>\n",
       "      <td>0.561403</td>\n",
       "      <td>-0.283585</td>\n",
       "      <td>-0.057771</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 300 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 0         1         2         3         4         5    \\\n",
       "1200       -0.638761 -1.032748 -0.235092 -0.424974 -0.232226  0.822992   \n",
       "cert        1.062055 -0.377882  0.104729  0.463845  0.262584 -0.365065   \n",
       "related    -0.004273 -0.443045  0.640763 -0.345597  0.122523  0.576840   \n",
       "artificial -0.381334 -0.306404  0.648571 -0.126388 -0.123929  0.320392   \n",
       "calculus   -0.247304 -0.327844 -0.156382 -0.447890  0.376691  0.275214   \n",
       "\n",
       "                 6         7         8         9      ...          290  \\\n",
       "1200        0.378264  0.139240  0.270665 -0.454389    ...     0.111120   \n",
       "cert       -0.061737 -0.226790  0.623428 -0.030326    ...    -0.319437   \n",
       "related    -0.175022  0.299697  0.165816 -0.234568    ...    -0.099955   \n",
       "artificial  0.162330 -0.216915  0.485710 -0.072828    ...    -0.508576   \n",
       "calculus    0.127010  0.901065  0.539872 -0.773755    ...    -0.041095   \n",
       "\n",
       "                 291       292       293       294       295       296  \\\n",
       "1200        0.414765  0.284807 -0.556309  0.560266  0.236525 -0.376341   \n",
       "cert       -0.404249  0.319670 -0.123425  0.190857  0.158566  0.025808   \n",
       "related    -0.034384 -0.077073 -0.117772  0.584124  0.348149  0.085304   \n",
       "artificial  0.065971  0.300530  0.151014 -0.175000 -0.197794  0.076596   \n",
       "calculus   -0.453284  0.199223 -0.029136  0.237765  0.179573  0.189013   \n",
       "\n",
       "                 297       298       299  \n",
       "1200        0.360399 -0.321175 -0.211022  \n",
       "cert       -0.487723 -0.201767  0.013518  \n",
       "related     0.215114  0.599803  0.631225  \n",
       "artificial -0.275751  0.313868 -0.356102  \n",
       "calculus    0.561403 -0.283585 -0.057771  \n",
       "\n",
       "[5 rows x 300 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.manifold import TSNE\n",
    "import _pickle as pickle\n",
    "\n",
    "tsne_input = word_vectors.drop(spacy.en.English.Defaults.stop_words,errors='ignore')\n",
    "tsne_input.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "tsne_file = 'tsne_models'\n",
    "tsne_vectors_file = 'tsne_vectors.npy'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "tsne = TSNE()\n",
    "tnse_vectors = tsne.fit_transform(tsne_input.values)\n",
    "with open(tsne_file, 'wb') as f:\n",
    "    pickle.dump(tsne,f)\n",
    "    \n",
    "pd.np.save(tsne_vectors_file,tnse_vectors)\n",
    "\n",
    "with open(tsne_file,'rb') as f:\n",
    "    tnse = pickle.load(f)\n",
    "tnse_vectors = pd.np.load(tsne_vectors_file)\n",
    "\n",
    "tnse_vectors = pd.DataFrame(tnse_vectors,index = pd.Index(tsne_input.index),columns=['x','y'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                    x          y        word\n",
      "1200         9.161677  -1.133896        1200\n",
      "cert        -5.911982  11.042277        cert\n",
      "related    -11.453212   6.534602     related\n",
      "artificial   8.312003   8.665087  artificial\n",
      "calculus     8.731849   5.540280    calculus\n",
      "               x         y    word\n",
      "python  3.141652 -1.677193  python\n"
     ]
    }
   ],
   "source": [
    "tnse_vectors['word'] = tnse_vectors.index\n",
    "print(tnse_vectors.head())\n",
    "print(tnse_vectors[tnse_vectors['word']=='python'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
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       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.6.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.6.min.css\");\n",
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       "\n",
       "  if (window._bokeh_is_loading === 0) {\n",
       "    console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "    run_inline_js();\n",
       "  } else {\n",
       "    load_libs(js_urls, function() {\n",
       "      console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "      run_inline_js();\n",
       "    });\n",
       "  }\n",
       "}(this));"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from bokeh.plotting import figure, show, output_notebook\n",
    "from bokeh.models import HoverTool, ColumnDataSource, value\n",
    "\n",
    "output_notebook()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <div class=\"bk-plotdiv\" id=\"4f1e1f53-d0f0-4d7c-a182-761b04f8c79d\"></div>\n",
       "    </div>\n",
       "<script type=\"text/javascript\">\n",
       "  \n",
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       "  \n",
       "    var force = false;\n",
       "  \n",
       "    if (typeof (window._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
       "      window._bokeh_onload_callbacks = [];\n",
       "      window._bokeh_is_loading = undefined;\n",
       "    }\n",
       "  \n",
       "  \n",
       "    \n",
       "    if (typeof (window._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "      window._bokeh_timeout = Date.now() + 0;\n",
       "      window._bokeh_failed_load = false;\n",
       "    }\n",
       "  \n",
       "    var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "       \"<div style='background-color: #fdd'>\\n\"+\n",
       "       \"<p>\\n\"+\n",
       "       \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "       \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "       \"</p>\\n\"+\n",
       "       \"<ul>\\n\"+\n",
       "       \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "       \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "       \"</ul>\\n\"+\n",
       "       \"<code>\\n\"+\n",
       "       \"from bokeh.resources import INLINE\\n\"+\n",
       "       \"output_notebook(resources=INLINE)\\n\"+\n",
       "       \"</code>\\n\"+\n",
       "       \"</div>\"}};\n",
       "  \n",
       "    function display_loaded() {\n",
       "      if (window.Bokeh !== undefined) {\n",
       "        var el = document.getElementById(\"4f1e1f53-d0f0-4d7c-a182-761b04f8c79d\");\n",
       "        el.textContent = \"BokehJS \" + Bokeh.version + \" successfully loaded.\";\n",
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       "        setTimeout(display_loaded, 100)\n",
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       "  \n",
       "    function run_callbacks() {\n",
       "      try {\n",
       "        window._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
       "      }\n",
       "      finally {\n",
       "        delete window._bokeh_onload_callbacks\n",
       "      }\n",
       "      console.info(\"Bokeh: all callbacks have finished\");\n",
       "    }\n",
       "  \n",
       "    function load_libs(js_urls, callback) {\n",
       "      window._bokeh_onload_callbacks.push(callback);\n",
       "      if (window._bokeh_is_loading > 0) {\n",
       "        console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "        return null;\n",
       "      }\n",
       "      if (js_urls == null || js_urls.length === 0) {\n",
       "        run_callbacks();\n",
       "        return null;\n",
       "      }\n",
       "      console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "      window._bokeh_is_loading = js_urls.length;\n",
       "      for (var i = 0; i < js_urls.length; i++) {\n",
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       "        s.onreadystatechange = s.onload = function() {\n",
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       "          if (window._bokeh_is_loading === 0) {\n",
       "            console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "            run_callbacks()\n",
       "          }\n",
       "        };\n",
       "        s.onerror = function() {\n",
       "          console.warn(\"failed to load library \" + url);\n",
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       "        console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
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       "    if (element == null) {\n",
       "      console.log(\"Bokeh: ERROR: autoload.js configured with elementid '4f1e1f53-d0f0-4d7c-a182-761b04f8c79d' but no matching script tag was found. \")\n",
       "      return false;\n",
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       "  \n",
       "    var js_urls = [];\n",
       "  \n",
       "    var inline_js = [\n",
       "      function(Bokeh) {\n",
       "        (function() {\n",
       "          var fn = function() {\n",
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Application\",\"version\":\"0.12.6\"}};\n",
       "            var render_items = [{\"docid\":\"90118a91-a173-4c9a-b909-3ae953e3a003\",\"elementid\":\"4f1e1f53-d0f0-4d7c-a182-761b04f8c79d\",\"modelid\":\"706fecf7-10a0-4eb0-9d81-cfc35790b0c9\"}];\n",
       "            \n",
       "            Bokeh.embed.embed_items(docs_json, render_items);\n",
       "          };\n",
       "          if (document.readyState != \"loading\") fn();\n",
       "          else document.addEventListener(\"DOMContentLoaded\", fn);\n",
       "        })();\n",
       "      },\n",
       "      function(Bokeh) {\n",
       "      }\n",
       "    ];\n",
       "  \n",
       "    function run_inline_js() {\n",
       "      \n",
       "      if ((window.Bokeh !== undefined) || (force === true)) {\n",
       "        for (var i = 0; i < inline_js.length; i++) {\n",
       "          inline_js[i](window.Bokeh);\n",
       "        }if (force === true) {\n",
       "          display_loaded();\n",
       "        }} else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(run_inline_js, 100);\n",
       "      } else if (!window._bokeh_failed_load) {\n",
       "        console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "        window._bokeh_failed_load = true;\n",
       "      } else if (force !== true) {\n",
       "        var cell = $(document.getElementById(\"4f1e1f53-d0f0-4d7c-a182-761b04f8c79d\")).parents('.cell').data().cell;\n",
       "        cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "      }\n",
       "  \n",
       "    }\n",
       "  \n",
       "    if (window._bokeh_is_loading === 0) {\n",
       "      console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "      run_inline_js();\n",
       "    } else {\n",
       "      load_libs(js_urls, function() {\n",
       "        console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "        run_inline_js();\n",
       "      });\n",
       "    }\n",
       "  }(this));\n",
       "</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_data = ColumnDataSource(tnse_vectors)\n",
    "# create the plot and configure the\n",
    "# title, dimensions, and tools\n",
    "tsne_plot = figure(title=u't-SNE Word Embeddings',\n",
    "                   plot_width = 800,\n",
    "                   plot_height = 800,\n",
    "                   tools= (u'pan, wheel_zoom, box_zoom,'\n",
    "                           u'box_select, resize, reset'),\n",
    "                   active_scroll=u'wheel_zoom')\n",
    "\n",
    "# add a hover tool to display words on roll-over\n",
    "tsne_plot.add_tools( HoverTool(tooltips = u'@word') )\n",
    "\n",
    "# draw the words as circles on the plot\n",
    "tsne_plot.circle(u'x', u'y', source=plot_data,\n",
    "                 color=u'blue', line_alpha=0.2, fill_alpha=0.1,\n",
    "                 size=10, hover_line_color=u'black')\n",
    "\n",
    "# configure visual elements of the plot\n",
    "tsne_plot.title.text_font_size = value(u'16pt')\n",
    "tsne_plot.xaxis.visible = True\n",
    "tsne_plot.yaxis.visible = True\n",
    "tsne_plot.grid.grid_line_color = None\n",
    "tsne_plot.outline_line_color = None\n",
    "\n",
    "# engage!\n",
    "show(tsne_plot);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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W1XlJLqXprX9sx/iPB7YB+qvq4RHSOQz4Ec3muCu0988Gvgf8GNgFeCpNv/9/Bl5UVfe2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NAAAg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\nX5IkSZIkSZKkAfP/jeVQRlnmQhEAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7feb64c18ac8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "from scipy.cluster.hierarchy import dendrogram, linkage\n",
    "\n",
    "l=linkage(res2vec.wv.syn0[0:50],method='complete',metric='seuclidean')\n",
    "\n",
    "plt.figure(figsize=(25,10))\n",
    "dendrogram(\n",
    "l,leaf_rotation=0,leaf_font_size=16,orientation='left',leaf_label_func=lambda v:str(res2vec.wv.index2word[v]))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "55\n"
     ]
    }
   ],
   "source": [
    "from sklearn.cluster import KMeans\n",
    "\n",
    "\n",
    "word_vectors = res2vec.wv.syn0\n",
    "print(int(word_vectors.shape[0]/100))\n",
    "num_clusters = int(word_vectors.shape[0]/100)\n",
    "\n",
    "# Initalize a k-means object and use it to extract centroids\n",
    "kmeans_clustering = KMeans( n_clusters = num_clusters )\n",
    "idx = kmeans_clustering.fit_predict( word_vectors )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Cluster: 0\n",
      "['discussion']\n",
      "\n",
      "Cluster: 1\n",
      "['1,000', 'attendee', 'host']\n",
      "\n",
      "Cluster: 2\n",
      "['patterns', 'oo', 'multithreading']\n",
      "\n",
      "Cluster: 3\n",
      "['light', 'pro', 'macros', 'studios', 'languag', 'rup', 'ms', 'salesforce', 'embarcadero', 'photoshop', 'pivot', 'drupal', 'works', 'simulink', 'powershell', 'tobii', 'mysql', 'familiar', 'bluemix', 'solvertable', 'lucid', 'rstudio', 'captivate', 'google', 'packet', 'axure', 'powerpoint', 'maps', 'visible', 'palisade', 'miscellaneous', 'autodesk', 'pspice', 'dreamweaver', 'explorer', 'arduino', 'modeler', 'assembly', 'itsm', 'excel', 'fiddler', 'files', 'antivirus', 'spss', 'word', 'verilog', 'robot', 'sas', 'precisiontree', 'lynda.com', 'office', 'snagit', 'suites', 'matlab', 'webex', 'lucidchart', 'visio', 'adwords', 'xcode', 'navigator', 'serena', 'arcgis', 'paint', 'proficiency', 'rose', 'parametric', 'proficient', 'stat', 'modeling', 'graphics', 'notes', 'acrobat', 'illustrator', 'prolog', 'visual', 'citrix', 'avaya', 'sqa', 'workbench', 'outlook', 'imaging', 'inventor', 'bloomberg', 'tools', 'draw', 'solver', '@risk', 'ooad', 'precision', 'tableau', 'sql*plus', 'wireshark', 'biweekly', 'skills', 'tbs', 'frontpage', 'studio', 'paradigm', 'autocad', 'bmc', 'media', 'spreadsheet', 'stattools', 'virtualbox', 'proteus', 'minute', 'jigsaw', 'rational', 'suite', 'abode', '365', 'opera', 'creo', 'analyzer', 'charts', 'netscape', 'tables', 'ocaml', 'minitab', 'arena', 'chrome', 'ie', 'lotus', 'salesforce.com', 'adobe', 'flash', 'c++', 'macromedia', 'stata', 'keil', 'python', 'microsoft', 'tracer', 'servicenow', 'docs', 'charles', 'remedy', 'mobizen', 'jmp', 'sharepoint']\n",
      "\n",
      "Cluster: 4\n",
      "['imagery', 'vector', 'motion', 'depict', 'projection']\n",
      "\n",
      "Cluster: 5\n",
      "['400', 'trainer', 'info', 'attract', 'reception', '60', 'contact', 'shore', 'liaise', '⃰', 'staff', 'prospective', 'blue', 'supervision', 'budgeting', 'talent', 'counsel', 'doctor', 'previously', 'supervised', 'infotech', 'placement', 'kronos', 'worker', 'faculty', 'supervise', 'reservation', '19', 'receptionist', 'hris', 'coordinator', 'dining', 'people', 'interview', 'coach', 'train', 'hour', 'boarding', 'recruitment', 'background', 'permanent', 'trip', 'ymca', 'incentive', 'recruit', 'resume', 'treat', '20', 'hire', 'mentored', 'nursing', 'junior', '90', 'hiring', 'cooperate', 'workforce', 'employee', 'orientation', 'person', 'mentor', 'coworker', '2014-december', 'screening', 'teller', 'fill', 'efficiently']\n",
      "\n",
      "Cluster: 6\n",
      "['standards', 'consolidation', 'article', 'understanding', 'evolve', 'session', 'audience', 'summary', 'reliability', 'align', 'recommendation', 'functional', 'milestone', 'responsibility', 'verse', 'cases', 'verification', 'feedback', 'iterative', 'input', 'dependency', 'derive', 'clarification', 'followed', 'finalize', 'guideline', 'standardize', 'best', 'simplify', 'actively', 'expectation', 'put', 'communicate', 'traditional', 'convey', 'kyc', 'optimal', 'adherence', 'business', 'assumption', 'wbs', 'sdlc', 'throughout', 'retrospective', 'exposure', 'determine', 'maximum', 'formulate', 'fulfill', 'owner', 'compliant', 'implication', 'matter', 'instruction', 'fit', 'life', 'white', 'strategy', 'refer', 'i.e.', 'governance', 'prioritize', 'cutover', 'assurance', 'offshore', 'processes', 'proposal', 'walkthrough', 'evaluation', 'criterion', 'actual', 'engineered', 'specifications', 'scrum', 'srs', 'identification', 'subject', 'diagrams', 'continuity', 'categorize', 'metrics', 'better', 'pathway', 'sessions', 'context', 'dimension', '⦁', 'analysis', 'phase', 'against', 'detail', 'groom', 'skilled', 'prism', 'qa', 'dictionary', 'shape', 'sow', 'adept', 'smooth', 'knowledge', 'uat', 'strategies', 'upcoming', 'prior', 'actionable', 'delivery', 'engage', 'deadline', 'existing', 'stakeholder', 'brd', 'result', 'rtm', 'deliver', 'convention', 'feasibility', 'strict', 'inception', 'onshore', 'conform', 'structure', 'readiness', 'scorecard', 'departmental', 'results', 'adhere', 'elicit', 'impact', 'super', 'color', 'msrb', 'sat', 'baseline', 'periodic', 'final', 'interpret', 'effort', 'cfo', 'conceptual', 'lifecycle', 'dive', 'directly', 'cio', 'gap', 'publication', 'intelligence', 'gathering', 'charter', 'estimation', 'standardized', 'acceptance', 'practice', 'propose', 'closely', 'participate', 'concise', 'note', 'ccb', 'expedite', 'complex', 'agree', 'consultation', 'facilitate', 'collaborate', 'revise', 'test', 'target', 'definition', 'integral', 'star', 'composer', 'guide', 'judicial', 'jad', 'completion', 'plan', 'supplementary', 'survey', 'carry', 'conducted', 'enhancement', 'direction', 'webinar', 'story', 'ceo', 'e2e', 'hoc', 'spec', 'level', 'expert', 'depth', 'vary', 'identify', 'standard', 'requirement', 'newly', 'present', 'progress', 'mechanic', 'initial', 'reviewed', 'cycle', 'alternative', 'overall', 'coordination', 'draft', 'assess', 'quality', 'methodology', 'planning', 'approach', 'profiling', 'easy', 'assure', 'freddie', 'prepared', 'vision', 'scope', 'rfi', 'accord', 'formulation', 'waterfall', 'sop', 'produce', 'matrix', 'workplace', 'demo', 'deliverable', 'rice', 'meeting', 'method', 'execution', 'repeatable', 'refine', 'fulfil', 'documentation', 'hierarchy', 'objective', 'detailed', 'review', 'diagram', 'specification', 'elicitation', 'demos', 'analyze', 'analyse', 'each', 'stake', 'risk', 'sanity', 'selection', 'translate', 'guidance', 'visibility', 'architectural', 'constraint', 'define', 'team', 'case', 'timeline', 'plans', 'reviews', 'gathered', 'comprehensive', 'streamlined', 'areas', 'met', 'standup', 'flows', 'sme', 'discovery', 'backlog', 'formal', 'scenarios', 'condition', 'consistent', 'ea', 'breakdown', 'ahead', 'gather', 'stlc', 'traceability', 'periodically', 'requests', 'improvement', 'benchmark', 'entire', 'release', 'ready', 'emphasize', 'invest', 'designs', 'transition', 'early', 'technical', 'section', 'roadmap', 'defined', 'smoke', 'regular', 'requirements', 'compose', 'prioritization', 'understand', 'meet', 'conduct', 'sprint', 'metric', 'iteration', 'advice', 'scenario', 'estimate', 'specific', 'study', 'boundary', 'correctness']\n",
      "\n",
      "Cluster: 7\n",
      "['orient', 'goal', 'fully', 'commitment', 'adapt', 'yet', 'attention', 'dedicated', 'analytical', 'challenging', 'motivated', 'communicator', 'influence', 'capable', 'attain', 'technically', 'savvy', 'employment', 'think', 'demonstrate', 'recognition', 'building', 'references', 'recognize', 'positive', 'further', 'great', 'who', 'adaptable', 'adaptability', 'combine', 'forward', 'mind', 'strengthen', 'luther', 'consistently', 'passion', 'volunteering', 'colleague', 'friendly', 'electricity', 'e.', 'very', 'able', 'unique', 'starter', 'aptitude', 'among', 'synthesize', 'onboard', 'interests', 'recipient', 'competent', 'productive', 'preparer', 'provides', 'counseling', 'oral', 'fellow', 'ability', 'leadership', 'fast', 'professional', 'complicated', 'key', 'discipline', 'academic', 'awards', 'prove', 'persuasive', 'round', 'sound', 'du', 'douala', 'advocate', 'highly', 'supervisor', 'crisis', 'seek', 'offer', 'describe', 'attitude', 'accomplishment', 'overview', 'conflict', 'executable', 'while', 'newsletter', 'mentoring', 'supervisory', 'possess', 'cameroon', 'play', 'continued', 'player', 'pursue', 'always', 'creativity', 'independently', 'collaborative', 'qualifications', 'already', 'opportunity', 'learning', 'dedicate', 'challenge', 'practical', 'consensus', 'articulate', 'appreciation', 'give', 'wall', 'consult', 'continue', 'variety', 'making', 'man', 'award', 'presentation', 'thinking', 'brief', 'career', 'involvement', 'choi', 'valuable', 'solid', 'gain', 'interpersonal', 'culture', 'proven', 'classroom', 'term', 'advancement', 'delivered', 'flexibility', 'posses', 'verbal', 'say', '32', 'coo', 'entrepreneurial', 'exceptional', 'accomplish', 'simple', 'excellent', 'succeed', 'tackle', 'effective', 'hardwork', 'face', 'significant', 'innovation', 'flexible', 'ethic', 'motivation', 'diverse', 'position', 'success', 'innovative', 'parent', 'quick', 'navigate', 'stable', 'managerial', 'solve', 'good', 'achievement', 'rapidly', 'creative', 'successful', 'organization', 'excellence', 'towards', 'encourage', 'learner', 'strong', 'skill', 'idea', 'often', 'thorough', 'ideal', 'organizational', 'pressure', 'commit', 'effectively', 'communication', 'coaching', 'outstanding', 'deep', 'adoption', 'personal', 'healthy', 'situation', 'learn', 'enjoy', 'contribute', 'see', 'motivate', 'contribution', 'little', 'pace', 'education', 'extra', 'resident', 'internship', 'willing', 'expand', 'acuman', 'promote', 'teamwork', 'contracting', 'grasp', 'received', 'empower']\n",
      "\n",
      "Cluster: 8\n",
      "['installing', '10.3.6', 'cpu', 'upgradation', '11gr1', '10.3.5', '9.3', 'jdk', 'applied', 'pack', 'packs', 'version', 'oss', 'amdocs', 'gradation', '10.x', '8.1', 'upgrade', '9.2mp2', '8.1/9.2', '9.14', 'upgrades', '8.2', '9.x', 'was', 'upgrading', 'upgraded', '10.2', '9.2', 'patch', '10.3', 'sp3', 'apply', 'mix', '8.x']\n",
      "\n",
      "Cluster: 9\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['ssl', '\\uf0d8', 'reliable', 'timeout', 'dhcp', 'wire', 'pgp', 'isolate', 'proxy', 'smtp', 'telnet', 'igrp', 'datapower', 'port', 'pop', 'udp', 'virus', 'secured', 'nat', 'ipv6', 't3', 'routers', 'frame', 'juniper', 'switch', 'relay', 'cryptographic', 'retransmission', 'encryption', 'rip', 'pki', 'wins', 'rout', 'dmz', 'rc4', 'bind', 'netware', 'ssh', 'networking', 'distance', 'l2/l3', 'laptop', 'firewall', 'ospf', 'protocols', 'osi', 'printer', 'rsa', 'cryptography', 'https', 'openview', 'tcp', 'certificate', 'socket', 'router', 'bgp', 'voip', 'arp', 'ip', 'ethernet', 'atm', 'authentication', 'cli', 'routing', 'sftp', 'vlan', 'msc', 'catalyst', 'vsphere', 'vpn', 'http', 'dsl', 'wan', 'dossier', 'acl', 'cisco', 'spam', 'ipsec', 'dns', 'certificates', 'lan', 'linksys', 'network', 'forwarding', 'unreliable', 'des', 'password', 'switching', 'layers', 'protocol', 'datagram', 'nfs', 'transport', 'secure', 'securely', 'ids', 'nortel', 'blackberry', 'anti', 'ipv4', 'stp', 'eigrp', 'ftp']\n",
      "\n",
      "Cluster: 10\n",
      "['cto', 'fire', 'subcontractor', 'dealing', 'portability', 'disa', 'authorize', 'comprise', 'medical', 'compliance', 'tb', 'edward', 'un', 'dental', 'airline', 'safety', 'prime', 'general', 'direct', '25', 'billing', 'year', 'nsips', 'advisor', 'full', 'mr.', 'organic', 'employ', '20,000', 'equities', 'mortgage', 'hhs', 'fraud', 'irs', '30', 'debt', 'rfp', 'agencies', 'roughly', 'reserve', 'small', 'usaid', 'agency', 'finance', 'officer', 'duty', 'independent', 'department', 'cfs', 'enforcement', 'faa', 'hippa', 'bpa', 'records', 'clients’', 'headquarters', 'w', 'sponsor', 'civilian', 'primarily', 'property', 'medicaid', 'representatives', 'clinic', 'spearhead', 'projects', 'broad', 'information', 'govt', 'cncs', 'provider', 'resources', '18', 'aviation', 'partnership', 'assistance', 'directors', 'navy', 'retirement', 'institutional', 'occupational', 'staffing', 'tsp', 'auditor', 'novel', 'couple', '70', 'claim', 'range', 'therapy', 'charge', 'operational', 'remain', 'wealth', 'vast', 'portfolio', 'briefing', 'industry', 'fidessa', 'fte', 'augmentation', 'intranet', 'cms', 'banking', 'budget', 'near', 'grant', 'agreement', 'fsa', 'primary', '15', 'warehousing', 'ngo', 'oversight', 'ufms', 'seven', 'principal', 'u.', 'thirty', 'aggregation', 'leading', 'reimbursement', 'it', 'cooperative', 'educational', 'fund', 'eight', 'liability', 'programs', 'payer', 'oversee', 'expenditure', 'laser', 'negotiation', '40', 'blood', 'tpocs', 'pension', 'lead', 'global', 'oats', 'aspect', 'enrollment', 'interpreter', 'fdic', 'finra', 'former', 'presence', 'program', 'exit', 'firm', 'capital', 'aid', 'partner', 'vital', 'servicing', 'comply', 'housing', 'professionalism', 'institution', 'additional', 'doj', 'augment', 'accountable', 'healthcare', 'care', 'idiq', 'four', 'cybersecurity', 'initiative', 'relationship', 'facet', 'top', 'domestic', 'disability', 'globally', 'specialty', 'lending', '700', 'modernize', 'facility', 'clerical', 'ehr', 'contract', 'legal', 'ndms', 'government', 'approximately', 'hospital', 'employer', 'sba', 'salary', 'govern', '5', 'attorney', 'industrial', 'special', 'wide', 'affiliate', 'outreach', '250', '65', 'official', 'health', 'public', 'accountability', 'serve', 'trade', 'administrative', 'nine', 'overseas', 'associated', 'focu', 'telecom', 'clinician', 'joint', 'flight', 'contributed', 'sayyad', 'webnas', 'five', 'appointment', 'focus', 'designate', 'pmo', 'population', 'human', 'dot', 'accountant', '13', 'act', 'house', 'clearing', 'economic', 'secondary', 'regulatory', 'ten', 'supported', 'foreign', 'accounting', 'specialize', 'seat', 'director', 'deputy', 'trading', 'subsystem', 'markets', 'trail', 'qualification', 'overhaul', 'history', 'private', 'obligation', 'family', 'federal', 'rehabilitation', 'dex', 'stationery', 'brokerage', 'law', '/contribution', 'grc', 'executive', 'doc', 'regulation', 'isr', 'patient', 'individual', 'osha', 'financial', 'manpower', 'medicare', 'facilitation', 'three', 'far', 'entitlement', 'asian', 'dozen', 'eligibility', 'advisory', 'clinical', 'personnel', 'bnym', 'funds', 'funding', 'military', 'mandate', 'pharmacy', 'incorporated', 'strategist', 'petty', 'normal', 'relation', 'dod', 'corporate', 'but', 'separation', 'equity', 'accommodate', 'interim', 'insurance']\n",
      "\n",
      "Cluster: 11\n",
      "['related', 'sheet', 'like', 'must', 'orders', 'submission', 'extension', 'scheduling', 'read', 'task', 'document', 'corresponding', 'will', 'another', 'into', 'material', '’', 'spread', 'decomposition', 'sensitive', 'trs', 'statement', 'action', 'users', 'would', 'drawing', 'point', '’s', 'sccm', 'move', 'compile', 'drive', 'collect', 'assay', 'schematic', 'equipment', 'for', 'all', 'hundred', 'edit', 'relate', 'etc', 'tool', 'sops', 'managers', 'certain', 'operator', 'same', 'kranthikbheema@gmail.com', 'daily', 'inspection', '\\ue00c', 'mass', 'trial', 'onto', 'successfully', 'monitor', 'printing', 'do', 'edms', 'verify', 'centralize', 'major', 'cards', '10,000', 'other', 'vacation', 'activity', 'response', 'permission', 'cover', 'inventory', 'area', 'remove', 'such', 'up', 'folder', 'also', 'proper', 'register', 'field', 'well', 'operating', 'schedule', 'via', 'receipt', 'connect', 'correspondence', 'exchange', 'floor', 'ran', 'line', 'applicant', 'follow', 'packaging', 'perform', 'receive', 'membership', 'editing', 'assist', 'fedex', 'keeping', 'bpp', 'compilation', 'updating', 'completeness', 'tax', 'updated', 'pre', 'ecr', 'shipping', 'from', 'allocation', 'package', 'physician', 'registration', 'post', 'complete', 'conformance', 'synchronize', 'consolidate', 'medium', 'letter', 'systematic', 'number', 'report', 'branch', 'as', 'notification', 'submit', 'link', 'incorporate', 'add', 'brochure', 'description', 'download', 'redline', 'email', 'catalogue', 'file', 'allocate', 'introduce', 'back', 'monthly', 'renew', 'central', 'disconnect', 'generate', 'in', 'could', 'quarterly', 'signature', 'dashboards', 'recordkeeping', 'logo', 'of', 'new', 'recording', 'agent', 'part', 'control', 'unit', 'pdf', 'outline', 'nightly', 'check', 'site', 'library', 'transmittal', 'archive', 'properly', 'loader', 'per', 'submittal', 'repository', 'e.g.', 'simultaneous', 'modification', 'ccr', '3.50', 'internal', 'send', 'open', '02/10/2012', 'drink', 'functioning', 'and', 'change', 'label', 'this', 'ensure', 'a', 'tie', 'specify', 'permit', 'checkpoint', 'external', 'request', 'element', 'through', 'operate', 'out', 'print', 'reflect', 'restructure', '-PRON-', 'damage', 'prepare', 'processing', 'paperwork', 'automate', 'every', 'shipment', 'livelink', 'worksheet', 'kept', 'uploaded', 'updates', 'logging', '45', 'onboarding', 'vendor', 'blackboard', 'content', 'accordance', 'training', 'which', 'so', 'indexing', 'sort', 'style', 'type', 'circumstance', 'contain', 'catch', 'create', 'resource', 'minimize', 'unlock', 'manage', 'ewm', 'help', 'balance', 'across', 'management', 'distribution', 'modified', 'main', 'ghost', 'rare', 'upload', 'template', 'pertinent', 'ship', 'assemble', 'between', 'auditing', 'old', 'audited', 'function', 'many', 'hard', 'bulk', 'pay', 'binder', 'one', 'right', 'basis', 'update', 'available', 'fulfillment', 'merge', 'project', 'expense', 'website', 'user', 'entry', 'mail', 'drill', 'write', 'keep', '100%', 'ownership', 'archival', 'generation', 'collected', 'by', 'with', 'author', 'capture', 'artist', 'shop', 'outgoing', 'performed', 'cq', 'creation', 'time', 'reconcile', 'reference', 'checklist', 'editorial', 'ring', 'valid', 'item', '\\uf06e', 'accurate', 'copy', 'instrument', 'record', 'delete', 'work', 'thermo', 'manager', 'disseminate', 'share', 'required', 'usage', 'execute', 'approve', 'threshold', 'audit', 'transfer', 'remote', 'establish', 'match', 'pc', 'flow', 'assignment', 'an', 'order', 'visa', 'eco', 'within', 'responsible', 'integrity', 'calendar', 'easily', 'example', 'job', 'routine', 'petition', 'aggregate', 'date', 'materials', 'inside', 'bill', 'invoice', 'mrp', 'used', 'consistency', 'locate', 'need', 'storage', 'preparation', 'frequent', 'recent', 'gmp', 'pass', 'comet', 'these', 'provided', 'enforce', 'group', 'searching', 'merchandise', 'policy', 'mis', 'ita', 'weekly', 'allow', 'run', 'archiving', 'portion', 'manual', 'deletion', 'tracking', 'build', 'wachovia', 'approval', 'inclusion', 'classified', 'various', 'form', 'dashboard', 'addition', 'ecybermission', 'over', 'occasion', 'code', 'fiber', 'make', 'wise', 'track', 'invoices', 'fax', 'inspect', 'stage', 'support', 'administrate', 'workgroups', 'operation', 'database', 'panel', 'require', 'procedure', 'list', 'offsite', 'filing', 'process', 'tasks', 'include', 'applicable', 'account', 'freight', 'that', 'be', 'local', 'to', 'renewal', 'registry', 'dependent', 'replace', 'bookkeeping', 'oversaw', 'crud', 'trc', 'upkeep', '120', 'online', 'coordinate', 'original', 'maintenance', 'book', 'revision', 'set', 'layout', 'asset', 'system', 'raw', 'provide', 'rewrite', 'profile', 'created', 'the', 'on', 'inventori', 'handle', 'familiarize', 'developed', 'license', 'map', 'bom', 'current', 'picture', 'own', 'photo', 'underlie', 'manually', 'maintain', 'initiate', 'yearly']\n",
      "\n",
      "Cluster: 12\n",
      "['ipad', '■']\n",
      "\n",
      "Cluster: 13\n",
      "['swift', 'validator', '2000/', 'awt', 'html5', '1.6', 'jdk1.6', 'perl', 'xml', 'jstl', 'jsf', 'theme', 'nodejs', 'j', '1.3', 'frameworks', 'wsad', '2005/2008', 'ilog', 'ejb', 'udb', 'year(s', 'mdb', 'cascading', 'jsps', 'sheets', 'dhtml', 'languages', 'tag', 'joomla', 'gwt', 'applets', 'js', 'appway', 'j2ee', '1.5', 'wireframe', 'json', 'ext', 'css', 'jsp', 'javascript', 'css3', 'uml', 'icefaces', 'responsive', 'jmx', '1.1', 'cgi', 'dom', 'dojo', 'portlets', 'jasper', 'abap', 'ee', 'extjs', 'swings', 'jbuilder', 'rmi', 'faces', 'xhtml', 'page', 'spr', 'bean', 'servlet', 'j2me', 'javabeans', 'webapps', 'csr', 'php', '2.0', 'struts', 'servlets', 'strut', 'tiles', 'java', 'plugin', 'odbc', 'taglibs', 'beans', 'ajax', 'libraries', 'swing', '3.0', 'liferay', '1.2', 'bootstrap', '3.2', 'html', 'jquery', 'd3.js', 'markup', 'xsl', 'ejbs', 'angular', 'angularjs']\n",
      "\n",
      "Cluster: 14\n",
      "['oig', 'oaam', 'ohs', 'solr', 'federation', 'federated', 'webgate', 'products', 'privilege', 'reset', 'sign', 'bash', 'unified', 'roles', 'tivoli', 'provision', 'owsm', 'ldap', 'oes', 'saml', 'ps2', 'webcenter', 'oud', 'console', 'obiee', 'odsee', 'oif', 'sandbox', 'identity', 'ad', 'oid', 'odsm', 'manger', '11gr2', 'ps3', 'idm', 'directory', 'bi', 'tfim', 'oem', 'provisioning', 'realm', 'xpress', 'sso', 'vm', 'ovd', 'adapters', 'connector', 'sailpoint', 'kornshell', 'opensso', 'scala', 'kerberos', 'icloud', 'rbac', 'rpm', 'workflows', 'idam', 'angular.js', 'practices', 'velocity', 'disable', 'oam', 'oim', 'plugins', 'iiq', 'cramer', 'isam', 'publisher', 'assertion', 'accessgate', 'ofsll', 'spml', 'ha']\n",
      "\n",
      "Cluster: 15\n",
      "['224', 'bheema', '20740', 'zgoldman@terpmail.umd.edu', '3.00', '626', '300', 'reiz', '310', 'college-', '201', '571', 'circle', 'rhode', 'kranthi', '3345', 'anne', '318', '860', 'rowalt', 'island', '48th', 'rd', '825', '330', 'chevy', 'tanvi', 'ph', '3102920250@pm.sprint.com', 'arundel', 'aflac', 'avenue', '20770', '|', 'street', 'md', '262', '422', '=', 'rockville', 'phone', '469', '202', '3412', '919', 'hyattsville', 'comm', 'apt', '9111', '702', '301', 'ctec', '\\uf09f', '9530', '368', 'shah', 'murphy', '►', 'mailing', 'tulane', '412', '520', 'silver', '443', 'bethesda', '638', '1276', '703', '410', '9.000', '♦', '720', 'linkedin', '4324', '8125', '1660', 'edmonston', 'ray', '292', 'park', '12.000', '\\x97\\uf097', 'http://daveray.net', 'christopher', '305', 'quail', '20783', '864', 'knox', 'ross', '75094', 'andrew', 'sms', 'ave', 'factgem', 'id', 'road', 'terrace', 'txt', 'lane', '101', 'jared', 'omega', 'tel', '7843', 'harris', '6.000', 'ellicott', 'engl', '550', 'rajan', 'subramanian', '323', '401', '||', '360', '640', 'david', 'potomac', '0250', '240']\n",
      "\n",
      "Cluster: 16\n",
      "['cfr', '21', 'fda']\n",
      "\n",
      "Cluster: 17\n",
      "['calculus', 'performer', 'mandarin', 'twice', 'photography', 'young', 'tutoring', 'korean', 'press', 'exercise', 'memorial', 'chinese', 'hovercraft', 'listen', 'diversity', 'professor', 'church', 'speak', 'repeat', 'tennis', 'cricket', 'sport', 'curriculum', 'publications', 'race', 'conversational', 'language', 'tournament', 'win', 'math', 'emerging', 'interest', 'village', 'swim', 'game', 'rural', 'english', 'awarded', 'varsity', 'french', 'girl', 'break', 'instruct', 'competition', 'child', 'literature', 'demonstration', '\\uf0a8', 'beginner', 'mathematic', 'german', 'fluent', 'hindi', 'writing', 'travel', 'obstacle', 'lesson', 'arrangement', 'artillery', '5%', 'athletic', 'art', 'matching', 'father', 'keen', 'teach', 'educate', 'fact', 'basketball', 'speaking', 'talk', 'qualified', 'elementary', 'tone', 'inner', 'teaching', 'scout', 'especially', 'bike', 'selected', 'awareness', 'painting', 'champion', 'individually', '▪', 'soccer', 'contest', 'leaders', 'teacher', 'native', 'tutor', 'gym', '1st', 'portuguese', 'medal', 'participant', 'camper', 'prize', 'running', 'honduras', 'examination', 'brazilian', 'peace', 'cmsc', 'camp', 'tutorial', '2nd', 'gold', '\\u200b-', 'counselor', 'african', 'magazine', 'haining', 'underprivileged', 'modern', 'hobby', 'speech', 'spanish', 'swimming', 'debate', 'craft', 'recreational', 'ball', 'russian', 'intermediate', 'reading', 'kid']\n",
      "\n",
      "Cluster: 18\n",
      "['1200', 'select', 'sigma', 'shelter', 'capstone', 'extracurricular', 'representative', '150', 'organizing', 'greet', 'hall', 'kappa', 'men', 'memberships', 'founding', 'seminar', 'holder', '200', 'football', 'fundraising', 'committee', 'pi', 'represent', 'youth', 'alumnus', 'wellness', 'phi', 'participation', 'concert', '2015-present', '34', 'founder', 'fitness', 'chair', 'welfare', '2013-present', 'leader', 'liaison', 'naamba', 'semester', 'arcelormittal', 'scholars', 'is', 'agenda', 'vesit', 'volunteer', 'primannum', 'performing', 'admission', 'vice', 'rotaract', 'lecture', 'visitor', 'forklift', 'iete', 'coordinated', 'fraternity', 'winter', 'unity', 'delta', 'treasurer', 'secretary', 'served', 'want', 'hurricane', 'foster', 'alpha', 'head', 'prince', 'umd', '500', 'admissions', 'past', 'flag', 'finalist', 'preside', 'blog', 'smsa', 'l&t', 'sorority', 'coordinating', 'adele', 'arrange', 'council', 'stamp', 'collegiate', 'student', 'organized', 'weekend', 'events', 'delegate', 'member', '99', 'fundraiser', 'elevator', 'social', 'board', 'reach', 'forum', 'lunch', 'environmental', 'attend', 'ace', '09/2014', 'summer', 'court', 'association', 'chapter', 'freshman', 'sports', 'ascend', 'quiz', 'charity', 'club', 'society', 'undergraduate', 'sharing', 'peer', 'students’', 'activities', 'invite', 'event', 'workshop', 'gsg', 'nu', '2013-', 'black', 'room', 'alumni', 'technician', 'conference', '2017-', 'union', 'crew', 'assistant', 'homecoming', 'howard', 'ambassador', 'multimedia', 'donation', 'golf', 'organizer', 'campus', 'cater', 'president', 'olympics', 'meal', 'beta', 'fall', 'recreation', 'woman', 'criminal', 'intramural', 'attended', 'league', '650', 'behavioral', 'apus', 'rise', 'community', 'tsan', 'philanthropy', 'students', 'chairman', 'affiliation', 'speaker', 'lifestyle', 'music', 'sustainability', 'homeless', 'organize']\n",
      "\n",
      "Cluster: 19\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['sep', 'mar']\n",
      "\n",
      "Cluster: 20\n",
      "['artificial', 'michigan', 'somaiya', 'bangalore', 'b.', 'b.tech', 'berkeley', 'hyderabad', 'k.', 'india', 'csi', '1995', 'autonomous', 'dwarkadas', 'jaypee', 'atlas', 'engineers', 'pune', 'r.', 'iit', 'kjsce', 'mechanical', 'sciences', 'mumbai', 'cgpa', 'fr', 'b.e', 'rodrigues', '16', 'praxis', 'ukraine', 'aas', 'cummins', 'california', 'sanghvi', 's.', 'technological', 'impetus', 'ukrainian', 'communications', 'bharat', 'ieee', 'natural', '1992', 'merit', 'women', 'surat', 'c.', 'noida', 'principle', 'electrical', 'jntu', 'manipal', '1996', 'james', 'maharashtra', 'engineering', 'electronics', 'pooma', 'telecommunications', 'srm', 'aerospace', 'b.e.', 'computer', 'srikant', 'k.j.', '1993', '1986', 'won', 'nagpur', 'technology-', 'physics', 'sagar', 'institute', 'm.', 'andhra', 'networks', 'j.', 'polytechnic', 'telecommunication', 'karnataka', 'a.', 'bombay', 'civil', 'w.', 'delhi', 'p.', 'indian', '1991', 'vellore']\n",
      "\n",
      "Cluster: 21\n",
      "['suggestion', 'sure', 'curtail', 'outside', 'turn', 'retest', 'pertain', 'satisfactory', 'notice', 'arrive', 'specified', '40%', 'less', 'not', 'trace', 'remotely', 'manner', 'again', 'reduce', 'swap', 'attachment', 'step', 'log', 'desk', 'resolve', 'desire', 'summarize', 'developers', 'chat', 'come', 'problem', 'next', 'tight', 'accurately', 'explain', 'concern', 'analysed', 'agreements', 'clarify', 'immediate', 'evidence', 'correction', 'determination', 'identified', 'any', 'escalation', 'caller', 'workaround', 'belzberg', 'troubleshot', 'discuss', 'interact', 'respective', 'mantech', 'call', 'priority', 'respond', 'affect', 'identifying', 'escalate', 'appropriately', 'readability', 'frequently', 'if', 'upper', 'exceed', 'deduction', 'honda', 'downtime', 'when', 'exception', 'prevention', 'bug', 'regard', 'telephone', 'before', 'minimal', 'narrow', 'naming', 'troubleshoot', 'title', 'encounter', 'important', 'whether', 'comment', 'or', 'issue', 'pssm', 'rent', 'error', 'possible', 'lease', 'diagnose', 'progression', 'without', 'aware', 'ne', 'hang', 'pick', 'arise', 'triage', 'indicate', 'timely', 'realistic', 'constant', 'patron', 'handover', 'almost', 'scr', 'short', 'stabilize', 'inform', 'bring', 'viability', '\\uf020', 'inquiry', '1500', 'crime', 'once', 'pain', 'particular', 'timeframe', 'difficult', 'during', 'corrective', 'deadlock', 'begin', 'adhoc', 'opening', 'sla', 'extinguisher', 'proactive', 'defect', 'forth', 'walk', 'free', 'tenant', 'status', 'emerge', 'trader', 'conclude', 'occur', 'and/or', 'moderate', 'there', 'ticket', 'fashion', 'know', 'address', 'stability', 'how', 'raise', 'prevent', 'prompt', 'initiation', 'emergency', 'correct', 'feel', 'satisfaction', 'turnaround', 'above', '95%', 'assisted', 'proactively', 'few', 'fee', 'refund', 'day', 'insure', 'ab', 'intervention', 'screenshot', 'quickly', 'accordingly', 'interaction', 'previous', 'regularly', 'tickets', 'pull', 'recur', 'necessity', 'miss', 'volume', 'forensic', 'root', 'complaint', '80%', 'depend', 'lock', 'personally', 'instrumental', 'kind', 'repetitive', 'inconsistency', 'ordinate', 'incident', 'malformed', 'outage', 'detect', 'advance', 'crash', 'either', 'maximo', 'warranty', 'finding', 'live', 'until', 'go', 'bottleneck', '24', 'most', 'whenever', 'appropriate', 'after', 'handled', 'smoothly', 'cc', 'activate', 'discrepancy', 'debugged', 'close', 'compiler', 'amount', 'no', 'guest', 'severity', 'employed', 'upon', 'pend', 'fix', 'notify', 'get', 'closure', 'handling', 'those', 'down', 'closing', 'reproduce', 'critical', 'about', 'resolution', 'investigate', 'repair', 'return', 'confirm', 'save', 'look', 'credit', 'illustrate', 'cause', 'failure', 'join', 'dap', 'deal', 'assign', 'payment', 'fixing', 'should', 'find', 'rca', 'late', 'lb', 'everyday', 'what', 'fab', 'temporary', 'take', 'necessary', 'deposit', 'question', 'stay', 'thereby', 'discover', 'here', 'overlap', 'push']\n",
      "\n",
      "Cluster: 22\n",
      "['cert', 'jdbc', 'tune', 'collection', 'factories', 'generic', 'enrol', 'memory', 'pools', 'configured', 'pool', 'adaptors', 'administered', 'idle', 'wldf', 'pools/', 'respect', 'sources', 'jms', 'jta', 'managing', 'dumps', 'bridges', 'outbound', 'jvm', 'message', 'optimum', 'argument', 'topics', 'size', 'sizes', 'dump', 'queues', 'diagnostic', 'bound', 'connectivity', 'jndi', 'adapter', 'modules', 'setting', 'concepts', 'sga', 'heap', 'topic', 'url', 'thread', 'threads', 'gc', 'partition', 'queue', 'destination', 'factory', '9.2/10', 'cache', 'eis', 'alias', 'aq', 'wizard', 'xa', 'leak', 'adjust', 'config', 'connections', 'garbage', 'stub', 'leaks', 'distributed', 'authenticator', 'connection', 'snmp']\n",
      "\n",
      "Cluster: 23\n",
      "['cincinnati', 'oh']\n",
      "\n",
      "Cluster: 24\n",
      "['iplanet', 'siteminder', 'novell', 'wily', '4.5', '9i', 'maestro', '10,shell', 'oracle9i', 'macintosh', 'jboss', 'jrockit', 'ubuntu', 'diagnostics', 'el', '6', 'bit', 'websphere', 'centos', '6.x', '1.4', 'red', 'emc', 'dos', '2000/xp', 'hyper', '3.1', '1.0', '8', 'mcafee', 'series', '9.2/10.0', 'balancer', '7.x', 'mqserie', 'f5', 'cics', 'nt', 'linux', 'solaris', 'workstation', 'iis', '6.1/7.0', 'os', 'jprobe', 'mq', 'vms', '5.1', 'symantec', 'flavor', 'apache', 'solaris10', '4.0', '10.3.x', 'scripting', 'ibm', 'windows', 'xp', 'minder', 'sitescope', 'webserver', '6.0', 'boss', 'edition', '5.5', 'netegrity', 'ga', '2.1', 'sunone', 'endeca', '7.1', '95', '10', '9', 'aix', 'me', '10.3/11', '6.2', 'sonic', '4.x', '5.x', 'glassfish', 'ux', '5.0', 'unix', 'vista', 'db2', '5.x/6.x', '7', 'ooa', 'ultra', 'cobol', 'jconsole', 'vmware', 'msie', 'wordpress', '10.0', '9.2.2', '9.2/10.3', 'safari', '7.0', '7.x/8.x', 'alfresco', 'nagios', 'introscope', '6.5', 'mvs', '8.5.5', 'plumtree', 'sun', '8/10', '64', 'rhel', 'sphere', '2.2', 'redhat', '6/7', 'firefox', '11.0', '2000', 'agents', '98', '6.x/7.x', 'mozilla', '4.2', 'oracle10', 'atg', '8.5', '5.1/6.0', '9/10', 'webmethods', 'z', '7.0/8.0', 'dell', 'tomcat', '2000/2003', 'v', 'hat', 'couchbase', 'window', 'eap', '10/8/7', 'platforms', '6.1', '2.x', '8.0', 'informix', 'gateway']\n",
      "\n",
      "Cluster: 25\n",
      "['graphtalk', 'clone', 'nationalcar.com', 'environments', 'caching', 'wls', 'components', 'infrastructure', 'migration', 'server', 'shutdown', 'teams', 'logic', 'capacity', 'environment', 'tar', 'configuration', 'recovery', 'sp', 'virtualization', 'workload', 'tuxedo', 'executed', 'war', 'shoot', 'alone', 'reorganization', 'sever', 'recycle', 'command', 'alert', 'domain', 'container', 'unclassified', 'prod', 'automatic', 'installation', 'binary', '24/7', 'clusters', 'centers', 'non', 'deploy', 'disaster', 'admin', 'heterogeneous', 'bss', 'tc', '24x7', 'standalone', 'tuning', 'bea', 'trouble', 'fine', 'logs', 'cluster', 'space', 'backup', 'balancing', 'runtime', 'disk', 'stop', 'instal', 'start', 'appliance', 'invoke', 'shooting', 'concurrent', 'deployment', 'aem', 'production', 'crp', 'failover', 'replication', 'pfizer', 'sizing', 'configure', 'jar', 'dev', 'hosting', 'fault', 'snapshot', 'scalability', 'virtual', 'availability', 'clustered', 'oltp', 'bourne', 'throughput', 'banyan', 'instance', 'atom', 'instances', 'wramc', 'patching', 'mission', 'administration', 'silent', 'nodes', 'restart', 'hot', 'recover', 'cm', 'restore', 'install', 'migrate', 'ongoing', 'managed', 'monitoring', 'debugging', 'administer', 'configuring', 'machines', 'hw', 'horizontal', 'standby', 'uptime', 'load', 'weblogic', 'rman', 'mlds', 'scripts', 'monitored', 'perspective', 'blade', 'physical', 'node', 'env', 'high', 'dpscs', 'deployed', 'cloning', 'stress', 'vertical', 'ksh', 'varied', 'shared', 'dip', 'fail', 'script', 'crontab', 'middle', 'troubleshooting', 'mode', 'startup', 'setup', 'rttt', 'auto', 'performance', 'ase', 'korn', 'servers', 'stack', 'plug', 'staging', 'rotation', 'logical', 'shell', 'stand', 'balanced', 'mirror', 'stag', 'dba', 'portlet', 'poll', 'extreme', 'dr', 'alamo.com', 'ear', 'cold']\n",
      "\n",
      "Cluster: 26\n",
      "['loaded', 'pump', 'purge', 'store', 'vsp', 'export', 'insert', 'convert', 'subscriber', 'rule', 'retrieve', 'wrote', '2.6', 'hud', 'golden', 'populate', 'mockup', 'origin', 'data', 'segregate', 'attribute', '837', 'dml', 'enter', 'menu', 'transaction', 'missing', '5010', 'some', 'bfs', 'dimensional', 'format', 'ansi', 'import', 'graphical', 'extremely', 'calculation', 'views', 'crosswalk', 'appraisal', 'netezza', 'duplicate', 'x12', 'dynamically', '276/277', 'sum', 'manipulation', 'correctly', 'automatically', 'text', 'queries', 'cleanse', 'engines', 'consolidated', 'scientist', 'mypi', 'nbc', 'aginity', 'towson', 'cdm', 'transmit', 'resa', 'mainly', 'then', 'claims', 'transform', 'construct', 'count', 'esri', 'reconciliation', 'translation', 'sec', 'redundancy', 'ods', 'nugenesis', 'expression', 'parse', 'ddl', 'datum', 'edi', 'schemas', 'structured', 'incom', 'hl7', 'flat', 'feed', 'validate', 'conditional', 'query', 'transformation', 'column', 'show', 'sequence', '835', 'answer', 'inbound', 'dynamic', 'manipulate', 'loading', 'cypher', 'written', 'character', 'unstructured', 'row', 'relational', 'extract', 'nfp', 'transactional', 'erd', 'p.l.a.n.', 'fetch', 'purpose', 'mask', 'dcl', 'dw', 'scrub', 'source', 'vuser', 'extraction', 'dms', 'historical', 'schema', 'mapping', 'clean', 'hipaa', '834', 'mark', 'neo4j', 'warehouse', 'amp', '270/271', 'icd', 'finally', 'edw', 'conversion', 'broker', 'replicate', 'fly', 'validation', 'correspond', '4010', 'table', 'parser', 'separate', 'lookup', 'refresh', 'index', 'split', 'normalization', 'generator', 'omni']\n",
      "\n",
      "Cluster: 27\n",
      "['wayne', 'ny', 'jane', 'memphis', 'raleigh', 'pa', 'east', '1985', 'clerk', 'f.', 'oxford', 'addison', 'winston', 'inc.', 'fort', 'williams', 'atlanta', 'jersey', 'boston', 'mn', 'worth', 'carolina', '1', 'york', 'nj', 'pittsburgh', '1987', 'ks', 'houston', 'tn', 'hotels', 'corp', 'johnson', 'georgia', 'bay', 'western', 'relations', 'christian', '1990', 'pacific', 'inc', 'thomas', 'daniel', 'system’', '1989', 'orleans', 'dallas', 'william', 'paul', '03/2012', 'fairfax', 'va', 'philadelphia', 'restaurant', 'nc', '1983', 'delaware', 'la', 'seattle', 'brothers', 'baltimore', 'vp', 'doe', 'st.', 'georgetown', 'city', 'syracuse', 'florida', 'milwaukee', 'chase', 'l.', 'maxim', 'avis', 'hospitals', 'usa', 'fl', 'texas', 'bloomington', 'greenbelt', 'joseph', 'kumar', 'tx', 'newark', '09/2012', 'contractor-', 'paradyme', 'miami']\n",
      "\n",
      "Cluster: 28\n",
      "['cassandra', 'cloudera', 'big', 'spark', 'node.js', 'hbase', 'yarn', 'pig', 'sqoop', 'hadoop', 'nosql', 'mapreduce', 'hdfs', 'spool', 'hive', 'impala']\n",
      "\n",
      "Cluster: 29\n",
      "['7.3', 'timesheet', 'sqr', 'om', 'terminate', 'accounts', '8.9', 'payable', 'treasury', 'clarity', 'tam', 'istore', 'encompass', 'sub', 'opm', 'recruiting', 'codes', 'accrual', 'ariba', 'darden', 'elements', 'nextel', 'ben', 'fscm', 'mss', 'compensation', '8.8', 'fi', 'roll', 'subcontract', 'ess', 'retro', 'lms', 'peoplecode', 'hcm', 'receivable', 'crm', 'soft', 't&l', 'epa', 'upk', 'delegation', 'clock', 'sd', 'ps', 'module', 'fixed', 'specifically', 'peoplesoft', 'workday', 'ap', 'vanilla', 'pp', 'earning', 'thru', 'payroll', 'leave', 'fico', 'self', 'rollout', 'mdm', 'adjustment', 'ftd', 'bpc', 'invoicing', 'procurement', 'otc', 'customization', 'ecc', '8.3', 'birlasoft', 'sbg', 'gl', 'hr', 'lm', 'purchasing', '8.51', '9.0', 'techno', 'sandia', 'po', 'par', 'absence', 'ledger', 'costing', 'na', 'mm', 'contracts', 'benefit', 'financials', 'benefits', 'responsibilities', 'labor', 'elm', 'ver', 'hrms', 'ar', 'eperformance', 'erecruit', 'r/3', 'wms', 'poi', '7.5', 'taleo', 'peopletools', '8.4', '9.1', 'adp', 'sales']\n",
      "\n",
      "Cluster: 30\n",
      "['bear', '$', 'period', 'secret', 'billion', 'australia', 'ireland', 'patrick', 'bakery', 'rome', 'taipei', 'de', 'trp', 'headquarter', 'manufacture', 'sergeant', 'wind', 'intra', '350', 'world', 'nyc', 'than', 'aim', 'twenty', 'half', 'france', 'nv', 'rank', 'sears', 'nuclear', 'airport', 'holiday', 'country', 'editor', 'larsen', 'retailer', '100', 'bond', 'patent', 'options', 'fitch', 'lot', 'bentonville', 'seed', 'disney', 'second', 'place', 'fiscal', 'south', 'ge', 'hsbc', '500,000', 'japan', 'fuel', 'home', 'beacon', 'first', 'latin', 'ridge', 'las', 'hanover', 'parking', 'pharmaceutical', 'm.d.', 'canada', 'holdings', '18f', 'wisconsin', 'dla', 'at&t', 'finish', 'abercrombie', 'european', 'last', 'são', 'hunter', '8,000', 'compete', 'outsourced', 'ever', '600', 'premier', 'animal', 'meadows', 'accept', 'soldier', 'hold', 'hope', 'residency', 'dr.', 'fifth', '300,000', 'edwards', '35', '450', '50', 'progressive', 'bagram', 'onsite', 'jd', 'newspaper', '4th', 'automotive', 'large', 'fellowship', 'fleet', 'abb', 'saudi', 'shift', 'found', 'europe', 'bradley', 'commission', 'array', 'quarter', 'jp', 'tenure', 'farm', 'monetary', 'congress', 'wafer', 'mianyang', 'buyer', 'conway', 'household', 'nearly', 'plant', 'fannie', 'jpmorgan', 'become', 'baptist', 'company', 'green', 'emerson', 'embassy', 'comp', 'prasad', 'fortune', 'subgroup', 'clark', 'around', 'subsidiary', 'location', 'bank', 'abroad', 'marathon', 'since', 'stearns', 'just', 'commander', 'taiwan', 'ct', 'mwh', 'two', 'donate', 'at', 'mexican', 'footprint', 'harvard', 'lighting', 'week', 'span', 'please', 'asia', 'manufacturer', 'nation', '5000', 'currently', 'money', 'hi', 'worldwide', 'north', 'ultimately', 'american', 'africa', 'dollar', 'korea', 'winner', 'children', 'sc', 'truck', 'op', 'kohl', 'abbott', '228', 'mexico', 'beverage', 'trailer', 'walmart', '80', 'baylor', 'epc', 'pediatric', 'visit', 'month', 'drug', 'co', 'relocate', 'cantor', 'warner', '>', '4,000', 'singapore', 'construction', 'nutrition', 'today', 'rock', 'only', 'mountain', 'assigned', 'mutual', 'dcs', 'bag', '6000', 'million', 'gurgaon', 'nestlé', '140', '23', 'england', 'brazil', 'automobile', 'nasdaq', 'west', 'entertainment', 'usd', 'nationwide', 'globe', 'bayer', 'paulo', 'cci', 'percent', '22', 'commercial', '1000', 'jump', 'clothing', 'working', 'supplier', 'manufacturing', 'manhattan', 'still', 'name', 'below', '75', 'least', 'gerber', '3rd', 'vegas', 'vietnam', 'grow', 'hill']\n",
      "\n",
      "Cluster: 31\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['3.8', 'honor', 'graduation', 'r.h.', 'm.s.', 'philosophy', 'msis', 'cum', 'mary', '0.00', 'indiana', 'laude', 'mba', 'ugrd', '2017', '12.00', 'candidate', '3.9', 'science', '3.7', 'illinois', 'isa', 'scholar', 'concentration', 'shonk', 'anticipate', '2018', 'endowed', 'economy', 'informatics', 'h.', 'iowa', 'chemistry', 'sociology', '3.5', 'economics', '2019', 'moscow', 'ernst', 'macroeconomics', 'colorado', 'psychology', 'smith', 'hunan', 'citation', 'cumulative', 'university', 'entrepreneurship', 'college', 'keller', 'graduated', 'umbc', 'bowie', 'maryland', 'b.s.', 'summa', 'russia', 'intro', 'gpa', 'expect', 'bachelor', 'pennsylvania', 'school', 'deans', 'dean', 'distinction', 'ann', '3.3', 'technology‐bs', 'honors', 'gmat', 'blacksburg', '16.00', 'graduate', 'george', 'cohort', 'diploma', 'standing', 'studies', 'degree', '3.6', '4.0/4.0', 'master', 'cs', 'biology', 'arts', '3.6/4', 'indianapolis', 'scholarship', 'bs', 'fellows', 'b.s', 'minor', 'ba', 'totals', 'specialization', 'methods', 'political', 'double', 'masters', 'academy', 'statistics', 'gre', '3.4', 'robert', 'mathematics', 'b.a.', 'mason']\n",
      "\n",
      "Cluster: 32\n",
      "['protection', 'rar', 'artifact', 'sa', 'border', 'deficiency', 'ciso', 'ice', 'directive', 'customs', 'mitigation', 'nist', 'categorization', 'ato', 'routinely', 'fisma', 'hrci', 'unauthorized', 'canadian', 'ssp', 'threat', 'hardening', '800', 'posture', 'assessments', 'csam', 'poa&m', 'authority', 'audits', 'scanning', 'following', 'scan', 'isso', 'cp', 'pta', 'authorization', 'a&a', 'ferpa', 'privacy', 'pci', 'abac', '37', 'contingency', 'security', 'remediate', 'ra', 'fips', '199', 'protect', 'proceeding', 'remediation', 'mitigate', 'assessment', 'weakness', 'sox', 'poa&ms', 'milestones', 'vulnerability', 'clearance', 'c&a', 'nessus', 'trusted', 'st&e']\n",
      "\n",
      "Cluster: 33\n",
      "['obtain', 'body', 'structures', 'circuit', 'eat', 'sensor', 'bar', 'paper', 'door', 'rating', 'loop', 'region', 'planner', 'gps', 'reduction', 'measurement', 'interactive', 'laboratory', 'receiver', 'heat', 'resonate', 'projector', 'video', 'webpage', 'terminal', 'iot', 'gas', 'discrete', 'abbvie', 'digital', 'lab', 'smartphone', 'static', 'thousand', 'partial', 'gift', 'cas', 'constituent', 'samsung', 'difference', 'com', '∙', 'mechanism', 'measure', 'thing', 'habit', 'density', 'where', 'circuits', 'pcb', 'camera', 'compression', 'analog', 'ordering', 'reader', 'can', 'tower', 'graphic', 'auxiliary', 'peripheral', 'voice', 'disposal', 'wireless', 'biomedical', 'magnetic', '3d', 'gear', 'transmitter', 'intend', 'bluetooth', 'surveillance', 'desktop', 'persistent', 'attack', 'techniques', 'issn', 'filter', 'kalman', 'intuitive', 'controllers', 'rebuild', 'tea', 'emv', 'iphone', 'movement', 'publish', 'bed', 'ride', 'scanner', 'display', 'surplus', 'era', 'compensate', 'counter', 'microcontroller', 'programmed', 'card', 'pulse', 'navigation', 'energy', 'fabrication', 'scheme', 'inspector', 'pts', 'bitbyte', 'cadence', 'reward', 'temperature', 'instrumentation', 'traffic', 'based', 'power', 'meter', 'incoming', 'pwm', 'efficient', 'output', 'electronic', 'hub', 'detection', 'symbol', 'optical', 'intelligent', 'attach', 'debit', 'computing', 'alarm', 'checkout', 'dispatch', 'limit', 'completely', 'audio', 'simulator', 'chip', 'devices', 'controller', 'tablet', 'mathematical', 'booking', 'transmission', 'urban', 'epic', 'cable', 'journal', 'scientific', 'satellite', 'smart', 'seller', 'bio', 'theory', 'replacement', 'waste', 'verifone', 'handheld', 'vr', 'modem', 'ncr', '8051', 'emulator', 'weight', 'toolbox', 'intrusion', 'voltage', 'device', 'wheel', 'ticketing', 'kernel', 'processor', 'lose', 'ir', 'introduction', 'detector', 'image', 'ingenico', 'way', 'hardware', 'mount', 'xerox', 'motor', 'stripe', 'cat', 'latency', 'stitching', 'vehicle', 'django', 'compatible', 'vlsi', 'highlight']\n",
      "\n",
      "Cluster: 34\n",
      "['wiki', 'harvest', 'nexus', 'putty', 'galileo', 'hp', 'mockito', 'subversion', 'puppet', 'jenkin', 'splunk', 'jira', 'safe', 'cygwin', 'selenium', 'patrol', 'bac', 'atlassian', 'jmeter', 'bamboo', 'ide', 'wlst', 'log4j', 'artisan', 'rcp', 'rtc', 'uft', 'cvs', 'soapui', 'starteam', 'tdd', 'alm', 'netbeans', 'dynatrace', '11.5', 'mssql', 'samurai', 'hpqc', 'confluence', 'rally', 'quest', 'clearquest', 'pvcs', 'ci', 'ant', 'tortoise', 'docker', 'cucumber', 'rc', 'clear', 'gradle', 'udeploy', 'plus', 'jaws', 'chef', 'rapid', '12.5', 'adb', 'clearcase', '12.0', 'continuous', 'cruise', 'myeclipse', 'hpalm', 'runner', 'jobs', 'tibco', 'toad', 'intellij', 'nant', 'elementool', 'aqua', 'ems', 'testrail', 'vb', 'cruisecontrol', 'cd', 'devops', 'tfs', 'jython', 'firebug', 'webdriver', 'ruby', 'qtp', 'eclipse', 'vss', 'git', 'perforce', 'loadrunner', 'mantis', 'rail', 'autosys', 'mercury', 'sbm', 'methodologies', 'mtm', 'autonomy', 'bugzilla', 'debug', 'rad', 'junit', 'coldfusion', 'jenkins', 'installer', 'hook', 'pair', 'winscp', 'businessworks', 'ansible', 'cron', 'versioning', 'silk', 'github', 'filezilla', 'svn', 'artifactory', 'sit', 'testng', 'odm', 'winrunner', 'mgmt', 'radar', 'sts', 'maven', 'hudson', 'qc']\n",
      "\n",
      "Cluster: 35\n",
      "['ssi', 'o', 'si', 'u', 'y', 'e', 'ex', 'st', 'al', 'ic', 'er', 'x', 'i', 'rajvkk@yahoo.com', 'io', 'ist', 'en', 'h', 'p', 'c', 'ss', 't', 'exp', 'fair', 'm', 'l', '4.00', 'n', 'd', 's', 'b', 'rotary', 'f']\n",
      "\n",
      "Cluster: 36\n",
      "['ranking', 'probability', '30,000', 'predict', 'mining', 'visualization', 'comprising', 'neural', 'visualize', 'disease', 'plot', 'duke', 'mean', 'facebook', 'r', 'popularity', 'forest', 'variable', 'graph', 'acknowledge', 'prediction', 'trend', 'basket', 'decisions', 'vote', 'cleansing', 'comparison', 'age', 'nn', 'sentiment', 'choose', 'average', 'loan', 'cleaning', 'predictive', 'glm', 'movie', 'demographic', 'classification', 'glimmix', 'tree', 'sensitivity', 'score', 'curve', 'generalized', 'pattern', 'roc', 'huge', 'mine', 'k', 'quantitative', 'regression', 'confidence', 'anova', 'food', 'interesting', 'compare', 'transformational', 'chemical', 'logistic', 'water', 'twitter', 'hypothesis', 'random', 'knn', 'ingredient', '3000', 'presidential', 'statistical', 'cart', 'chart', 'model', 'linear', 'dbms', 'descriptive', 'dataset', '1900', 'classify', 'sample', 'bayes', 'technique', 'stores', 'popular', 'ยง', 'diamond', 'accident', 'filtering', 'mental', 'death', 'algorithm', 'models', 'correlation', 'machine', 'wine', 'birth', 'harness', 'coursera', 'modelling', 'geographic', 'seasonal', 'interval', 'exploratory', 'stock', 'indicator', 'trees', 'naïve', 'restatement', 'accuracy', 'cdc', 'algorithms', 'cuisine', 'observe', 'reviewer', 'useful', 'election']\n",
      "\n",
      "Cluster: 37\n",
      "['procedures', 'stored', 'triggers', 'trigger']\n",
      "\n",
      "Cluster: 38\n",
      "['lims', 'injection', 'virtually', 'pega', 'speed', 'mart', 'sim', 'single', 'mulesoft', 'along', 'dow', 'customize', 'coded', 'simultaneously', 'agile', 'extend', 'base', 'gmsec', 'driven', 'gccp', 'gis', 'drm', 'cot', 'customers', 'extensive', 'respectively', 'configurable', '+', 'pipeline', 'synchronization', 'r&d', 'expertise', 'software', 'pioneer', 'reverse', 'integrate', 'feeder', 'orpos', 'tiered', 'usability', 'vob', 'concept', '1.7', 'implement', 'premise', 'compatibility', 'use', 'login', 'develop', 'real', 'reside', 'ppm', 'token', 'utility', 'enhanced', 'object', 'sw', 'cross', 'layer', '3-tier', 'designing', 'embed', 'experience', 'automated', 'multi', 'apigee', 'prototyping', 'coe', 'datacenter', 'center', 'backend', 'specialized', 'complexity', 'queuing', 'nyse', 'core', 'view', 'internationalization', 'ivr', 'ood', 'grouping', 'screen', 'sap', 'retrofit', 'classmate', 'different', 'led', 'coding', 'gui', 'web', 'client-', 'platform', 'everything', 'interfac', 'involve', 'hand', 'functionality', '∙test', 'pilot', 'solution', 'utilize', 'jeppesen', 'emphasis', 'ordination', 'spot', 'architect', 'third', 'geographically', 'scratch', 'scalable', 'browser', 'credential', 'heavy', 'feature', 'whole', 'several', 'bcbs', 'undertaken', 'together', 'proof', 'prototype', 'localization', 'mobility', 'extensively', 'side', 'hana', 'shelf', 'optimized', 'intensive', 'catalog', 'bw', 'have', 'frontend', 'cbs', 'divide', 'capability', 'framework', 'netweaver', 'pacs', 'geographical', 'integrating', 'pos', 'isrweb', 'wallet', 'conceptualize', '3pl', '4', 'ios', 'dream', 'consist', 'addie', 'centralized', 'sync', 'combination', 'applications', 'spoe', 'android', 'tracker', 'entity', '○', 'oriented', 'front', 'oop', 'parallel', 'bridge', 'workflow', 'both', 'class', 'architecture', 'design', 'sdk', 'implemented', 'activation', 'architected', 'vault', 'party', 'leverage', '●', 'later', 'touch', 'built', 'jcl', 'distribute', 'downstream', 'reusable', 'celerkost™', 'common', 'box', 'hybrid', 'active', 'prototyped', 'application', 'cod', 'service', 'modular', 'refactor', 'hec', 'developer', 'experienced', 'development', 'skin', 'end', 'anywhere', 'arm', 'accessibility', 'rich', 'search', 'enterprise', 'multiple', 'disparate', 'standardization', 'proprietary', 'slt', 're', 'kit', 'batch', 'car', 'collaboration', 'edge', 'implementation', 'mid', 's/4', 'hands', 'intel', 'ease', 'appium', 'app', 'relocation', 'cad', 'access', '2', 'driver', 'component', 'product', 'converted', 'authenticate', 'enhance', 'role', 'conjunction', 'commerce', 'polymer', 'isd', 'broadband', 'simulations', 'customized', 'poc', 'sencha', 'automation', 'involved', 'technology', 'custom', 'fpars', 'sites', 'spirent', 'centric', 'azure', 'expose', 'under', 'engine', 'stream', 'api', 'enablement', 'testing', 'oms', 'integration', 'numerous', 'programming', 'interface', 'scm', 'micro', 'exist', 'legacy', 'd.b.a.', \"'s\", 'robust', 'redesign', 'fms', 'plm', 'scale', 'uperform', 'tier', 'mule', 'ecommerce', 'internet', 'ui', 'pm', 'mainframe', '3', 'geospatial', 'powerful', 'structural', 'idms', 'erp', 'client', 'integrated', 'cbt', '12', 'seamless', 'mobile', 'retrieval', 'enable', 'shopping', 'negative']\n",
      "\n",
      "Cluster: 39\n",
      "['option', '30%', 'competitive', 'long', 'entrepreneur', 'evaluate', 'lean', 'six', '\\uf0b7', 'delay', 'dealer', 'launch', 'proposition', 'venue', 'advise', 'bid', 'experiment', 'forecast', 'eac', 'feasible', 'quantity', 'advertising', 'reduced', 'conjoint', 'hotel', 'examine', 'revenue', 'consumer', 'preference', 'philips', 'tactic', 'eye', 'tayohya', 'advantage', 'adopt', 'conclusion', 'm&a', 'determined', 'suitable', 'insight', '90%', 'alignment', 'mapbox', 'alliance', 'market', 'profit', 'more', 'profitability', 'earn', 'quant', 'americas', 'sell', 'offering', 'customer', 'kpi', 'hospitality', 'acquire', 'zero', 'sourcing', 'marketplace', 'advertisement', 'commodity', 'cash', 'improvise', 'valuation', 'settlement', '12%', 'sized', '75%', 'incidence', 'promotional', 'force', 'purchase', 'square', 'mistake', '60%', 'buy', 'financing', 'engagement', 'brand', 'margin', '15%', 'price', 'l’oreal', 'optimize', 'value', 'thus', 'retail', 'toward', 'cr', 'conceptualized', 'qualitative', 'competitor', 'prospect', 'tactical', 'future', 'revamp', 'donco', 'recommend', 'dual', 'maker', 'choice', 'breach', 'expansion', 'investment', 'swot', 'suggest', 'metal', 'income', 'advised', '50%', 'characteristic', 'mixture', 'consumption', 'increase', 'spending', 'investor', 'pricing', 'quote', 'acquisition', 'promise', 'growth', 'variance', 'analytic', 'discount', 'rate', 'supply', 'infertility', 'rental', 'spend', 'explore', 'research', 'excess', 'roi', 'similar', 'loyalty', 'boost', 'negotiate', 'forecasting', 'devise', '\\uf0a7', 'strategic', 'limitation', 'meaningful', 'segment', 'category', 'demand', 'saving', 'news', 'potential', 'promotion', 'porter', 'efficiency', 'campaign', 'customers’', 'questionnaire', 'diligence', 'churn', 'continuously', 'fx', 'achieve', '10%', 'chain', 'improve', 'competency', 'figure', 'merger', 'earned', 'marketing', 'pitch', '100,000', 'algae', 'disclosure', 'total', '25%', 'derivative', 'segmentation', 'eliminate', 'sustainable', 'knowledgeable', 'sale', 'bounce', 'productivity', 'hughes', 'decision', 'retention', 'incur', 'dso', 'currency', 'estate', 'effectiveness', 'cut', 'streamline', 'decrease', 'cost', '20%', 'improved', 'maximize', 'futures', 'leveraged', 'coffee']\n",
      "\n",
      "Cluster: 40\n",
      "['hibernate', 'ioc', 'xpath', 'rest', 'restful', 'plane', 'rs', 'singleton', 'xslt', 'spring', 'ibatis', 'persistence', 'j2se', 'jmock', '508', 'jee', 'drools', 'mvc', 'microservice', 'dao', 'embedded', 'di', 'groovy', 'boingo', 'mongo', 'unload', 'jakarta', 'wsdl', 'binding', 'cxf', 'gemfire', 'axis', 'jpa', 'quartz', 'jaxb', 'aop', 'xsd', 'webservices', 'boot', 'uddi', 'ws', 'consume', 'abstract', 'sdkman', 'orm', 'activemq', 'sax', 'jaas', 'webservice', 'jax', 'annotation', 'orchestration', 'xquery', 'asynchronous', 'jaxp', 'soap']\n",
      "\n",
      "Cluster: 41\n",
      "['p6', 'mediator', 'r12', 'vordel', 'fmw', 'apex', 'bam', 'exadata', 'em', '10.1', 'soa', 'adf', 'osb', 'oracle11', 'fusion', 'db', 'goldengate', 'sqlserver', 'coherence', 'opatch', 'pentaho', 'apps', 'adaptive', 'viewer', '11.1.1.5', 'rdbms', '10g/11', 'rms', '12c', 'spatial', '11i', 'scom', 'b2b', 'oc4j', 'portals', 'rib', 'aqualogic', 'iq', 'guard', 'esb', 'rules', '2.5', '11g/', 'integrations', 'grid', 'g', 'bpel', 'mds', 'composite', 'oracle', 'suit', 'primavera', 'r2', 'jdeveloper', 'rcu', 'rel', 'oas', 'r3', 'middleware', 'msde', 'asm', '11g/12c', 'soa11', 'bpm', '8i', 'gate', 'ucm', '10gas', 'portal', 'ebusiness', 'timesten', '8i/9i/10', 'alsb', '12.1.3', '11.5.10', 'installed', 'bus', 'rpd', 'deploying', '9i/10g/11', 'alsr', 'veritas', '11', 'rac']\n",
      "\n",
      "Cluster: 42\n",
      "['itil', 'certify', 'pmi', 'hacking', 'v3', 'brain', 'cyber', 'maturity', 'scrummaster', 'years’', 'exam', 'course', 'comptia', 'advanced', 'logistics', '9001', 'analytics', 'ethical', 'foundation', 'relevant', '17', 'pmp', 'certification', 'certified', 'cmmi', 'courses', 'iv', 'iso', 'associate', 'workshops', 'professionals', '~', 'instructional', 'investigation', 'achieved', 'mcp', 'iii', 'a+', 'cmm', 'centre', 'essential', 'ii', 'fundamental', 'administrator', 'cissp', 'mac', 'generalist', 'helpdesk', 'coursework', 'mcse', 'ccna']\n",
      "\n",
      "Cluster: 43\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['annual', 'fest', 'cultural', 'year-', 'planned', 'sponsorship', 'inter', 'festival', 'semi']\n",
      "\n",
      "Cluster: 44\n",
      "['pages', 'jaspersoft', 'vs', 'net', 'flex', 'forms', 'olap', 'reports', 'erwin', 'parts', 'objects', 'debugger', 'bo', 'tm1', 'teradata', 'c#.net', 'quickbooks', 'documentum', 'discoverer', 'click', 'utilities', 'ssas', 'vba', 'graphs', 'publishing', 'instructor', 'intuit', 'pds', 'etl', 'pro*c', 'odi', 'cube', 'postgresql', 'bobi', 'caliber', 'powercenter', 'toolkit', 'mover', 'builder', 'scheduler', 'templates', 'powerbuilder', 'mongodb', '.net', 'addm', 'metadata', 'classic', 'ota', 'powerexchange', 'interfaces', 'integrator', 'xi', 'vb.net', 'databases', 'dynamics', 'controls', 'sybase', '97', 'asp', 'sql', 'awr', 'vbscript', 'datastage', 'telerik', 'reporter', 'plsql', 'ssis', 'cots', 'beyond', 'infopath', 'express', 'brio', 'ware', 'tsql', 'spy', 'cubes', 'c#.', 'informatica', '9i/10', 'powermart', 'crystal', 'modify', 'basic', 'macro', 'vugen', 'wcf', 'mf', 'designer', 'requisite', 'dts', 'reporting', 'ssrs', 'dfc', 'se', 'pl', 'microstrategy', 'cognos', 'asp.net', 'universe', 'packages', 'branding', 'hyperion', 'siebel', 'messaging']\n",
      "\n",
      "Cluster: 45\n",
      "['chicago', 'il']\n",
      "\n",
      "Cluster: 46\n",
      "['saic', 'mclean', 'universal', 'contractual', '2020', 'gsa', 'courts', 'madison', 'cristiano', 'john', 'senior', 'agriculture', '2014-present', 'state', 'goldman', '10/2007', 'cox', 'homeland', 'army', 'missouri', 'michael', 'ohio', 'mo', 'america', 'contractor', 'northern', 'cnsi', 'barney', '04/2005', 'brevard', 'zurich', 'massachusetts', 'orange', 'uspto', 'connecture', 'acs', 'naval', 'eds', 'arlington', 'citizenship', 'suitland', 'washington', '08/2015', 'hanoi', 'county', 'states', 'ups', 'virginia', 'researcher', 'beach', 'sra', 'nsa', 'creek', 'cerner', 'principles', 'jumpstart', 'district', 'mae', 'plano', 'fame', 'wa', 'regional', 'caci', 'justice', 'theater', 'columbia', 'sandy', 'schneider', 'noc', 'miller', 'arc', 'airlines', 'orlando', 'venture', 'transportation', 'dhhs', 'angeles', 'operations', 'uk', 'utah', 'eu', 'facilities', 'semiconductor', 'national', '513', 'usda', 'hopkins', 'morgan', 'nara', 'devry', 'u.s', 'plc', 'apple', 'immigration', 'affairs', 'southern', 'perot', 'lockheed', '10/2014', 'falls', 'irvine', 'modernization', 'symposium', 'johns', 'associates', 'fluor', 'lucent', 'annapolis', '05/2015', 'chamber', 'alexander', 'corporation', 'services', 'saba', 'cashier', 'tsa', 'corps', 'encore', 'teksystems', 'kansas', 'census', 'nations', 'ubs', 'd.c.', 'singh', 'walter', 'bothell', '14', 'us', 'specialist', 'austin', 'ops', 'bowes', 'solar', 'u.s.', 'dhs', 'greenville', 'cigna', 'veteran', 'pitney', 'now', 'marine', 'dubai', 'canvasser', 'electric', 'transit', 'nasa', 'united', 'chief', 'police', 'division', 'kaiser', 'systems', 'air', 'cap', 'nec', 'bureau', 'organizations', 'companies', 'defense', 'fbi', 'compaq', 'afghanistan', 'nhs', 'interior', 'alza', 'broadcom', '04/2015', 'industries', 'montgomery', 'zachary', 'pae', 'newport', 'wi', 'citizen', '11/2013', 'mcgraw', '10/2013', 'international', 'verizon', 'trust', 'dc', 'stanley', 'martin', 'lake', 'eagle', 'stamford', 'ia', 'amsd', 'kelly', 'dept', 'manager/']\n",
      "\n",
      "Cluster: 47\n",
      "['san', 'citigroup', 'dec', '2006', 'ltd.', 'clara', 'jr', 'jul', 'may', '2014', '2012-', 'june', '2002', 'valley', '2016', 'consultancy', 'portnov', 'dec.', 'bp', 'limited', 'sacramento', 'nike', 'oct.', '01', 'silicon', 'sr', '2010', 'feb', 'freelance', 'sunnyvale', '2016-', 'cognizant', 'technologies', 'minneapolis', 'project-', 'writer', 'mar.', 'spectrum', 'jan.', 'partners', 'columbus', 'packard', 'denmark', 'pvt', '2012', 'analyst', 'motors', 'gallagher', 'northrop', '2014-', 'fargo', 'trainee', 'endur', 'diego', 'q', 'irving', '2004', 'richmond', '04', 'sept.', 'reston', 'francisco', '1997', '2015-august', 'designation', '05', 'santa', '\\uf0f2', 'premium', '11/13', 'accenture', '2014-may', 'hcl', 'wells', 'ltd', 'labs', '’12', 'nov', 'ca', 'boeing', '2001', 'century', 'formerly', 'richardson', '1988', '2005', 'aug.', 'reuters', 'ma', 'jun.', 'brown', '2013', 'september', 'csc', 'apr.', '07', 'booz', '2008', 'apr', 'deloitte', 'satyam', '08', 'tech', 'odessa', 'nov.', '09/2013', 'comcast', 'programmer', 'till', '2015-', 'april', '\\u200b', 'securities', 'october', 'corp.', 'siemens', 'summit', 'aug', '02', 'infosys', '2015', 'hewitt', 'consultants', 'oct', '–may', 'laboratories', '2015-dec', 'january', '03', 'tester', 'intern', '2008-', 'hartford', 'jr.', 'dac', 'galaxy', 'hewlett', 'december', 'nokia', 'july', 'springfield', 'llc', 'jose', 'engineer', 'mahindra', 'prep', 'jun', 'wm', 'openlink', '10/16', 'november', 'los', 'altos', '2016-may', '2011-may', 'thomson', '1999', 'investments', 'jan', '1994', '2016-present', 'hamilton', 'consulting', 'bell', 'sept', '1998', 'fujitsu', 'chennai', 'march', 'alexandria', '2014-august', '2011', 'phoenix', '2013-may', 'az', 'august', 'analyst-', 'chantilly', 'chandigarh', '2003', 'allen', 'unisys', 'february', '09', '2009', 'hills', 'herndon', 'louis', 'co.', 'collierville', '2007', 'llp', 'oil', 'kpmg', 'solutions', 'tampa', 'rio', 'consultant', '06', 'tata', 'grumman', '2011-', 'wipro', '’13']\n",
      "\n",
      "Cluster: 48\n",
      "['clustering']\n",
      "\n",
      "Cluster: 49\n",
      "['propagation', 'off', 'strength', 'reuse', 'shadow', 'observation', 'parameter', 'utilization', 'block', 'nature', 'loss', 'treatment', 'consider', 'due', 'factor', 'tilt', 'effect', 'path', 'formula', 'grade', 'insertion', 'avoid', 'surround', 'fade', 'unnecessary', 'frequency', 'compute', 'calculate', 'statistic', 'interruption', 'drop', 'bsc', 'sector', 'antenna', 'low', 'outcome', 'signal', 'channel', 'amongst']\n",
      "\n",
      "Cluster: 50\n",
      "['lambda', 's3', 'amazon', 'ec2', 'scaling', 'sqs', 'aws', 'iam', 'elastic', 'dynamodb', 'route', '53', 'ecs', 'watch', 'rds', 'ebs', 'vpc', 'formation', 'saas', 'workspace', 'cloud']\n",
      "\n",
      "Cluster: 51\n",
      "['china', 'shanghai', 'beijing', 'hong', 'london', 'kong']\n",
      "\n",
      "Cluster: 52\n",
      "['huntsville', 'redstone', 'alabama']\n",
      "\n",
      "Cluster: 53\n",
      "['gm', 'detroit', 'mi']\n",
      "\n",
      "Cluster: 54\n",
      "['d.c', 'ericsson', 'coverage', '3-sectored', 'rf', 'planet', 'nearby', 'mentum', 'metro', 'downtown', 'carrier', 'cdma', 'behavior', 'cellular', 'mock', 'pcs', 'preliminary', 'wimax', 'radio', 'station', 'gsm', 'interference', 'umts', 'minimum', 'simulate', 'downlink', 'optimization', 'wave', 'suburb', 'poseidon', 'lte', 'simulation', '5.7', '\\xad', 'duration', 'microwave', 'wcdma', 'ofdm', '1c', 'stations', 'cell']\n"
     ]
    }
   ],
   "source": [
    "word_centroid_map = dict(zip( res2vec.wv.index2word, idx ))\n",
    "for cluster in range(0,num_clusters):\n",
    "    #\n",
    "    # Print the cluster number  \n",
    "    print (\"\\nCluster:\",cluster)\n",
    "    #\n",
    "    # Find all of the words for that cluster number, and print them out\n",
    "    words = []\n",
    "    for key,item in word_centroid_map.items():\n",
    "        if( item == cluster ):\n",
    "            words.append(key)\n",
    "    print(words)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "class MeanEmbeddingVectorizer(object):\n",
    "    def __init__(self, word2vec):\n",
    "        self.word2vec = word2vec\n",
    "        # if a text is empty we should return a vector of zeros\n",
    "        # with the same dimensionality as all the other vectors\n",
    "        self.dim = len(list(word2vec.values())[0])\n",
    "\n",
    "    def fit(self, X, y):\n",
    "        return self\n",
    "\n",
    "    def transform(self, X):\n",
    "        return np.array([\n",
    "            np.mean([self.word2vec[w] for w in words if w in self.word2vec]\n",
    "                    or [np.zeros(self.dim)], axis=0)\n",
    "            for words in X\n",
    "        ])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Pipeline(steps=[('word2vec vectorizer', <__main__.MeanEmbeddingVectorizer object at 0x7feb52267c88>), ('SVM', SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,\n",
      "  decision_function_shape=None, degree=3, gamma='auto', kernel='rbf',\n",
      "  max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
      "  tol=0.001, verbose=False))])\n",
      "Pipeline(steps=[('word2vec vectorizer', <__main__.MeanEmbeddingVectorizer object at 0x7feb506ac828>), ('extra trees', ExtraTreesClassifier(bootstrap=False, class_weight=None, criterion='gini',\n",
      "           max_depth=None, max_features='auto', max_leaf_nodes=None,\n",
      "           min_impurity_split=1e-07, min_samples_leaf=1,\n",
      "           min_samples_split=2, min_weight_fraction_leaf=0.0,\n",
      "           n_estimators=200, n_jobs=1, oob_score=False, random_state=None,\n",
      "           verbose=0, warm_start=False))])\n"
     ]
    }
   ],
   "source": [
    "from sklearn.svm import SVC\n",
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.ensemble import ExtraTreesClassifier\n",
    "import numpy as np\n",
    "\n",
    "w2v = dict(zip(res2vec.wv.index2word, res2vec.wv.syn0))\n",
    "\n",
    "etree_w2v = Pipeline([\n",
    "    (\"word2vec vectorizer\", MeanEmbeddingVectorizer(w2v)),\n",
    "    (\"extra trees\", ExtraTreesClassifier(n_estimators=200))])\n",
    "svm_w2v = Pipeline([\n",
    "    (\"word2vec vectorizer\", MeanEmbeddingVectorizer(w2v)),\n",
    "    (\"SVM\", SVC())])\n",
    "\n",
    "print(svm_w2v)\n",
    "print(etree_w2v)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['scripting' 'majors' 'scripting']\n"
     ]
    }
   ],
   "source": [
    "X=[['python','ocaml'],\n",
    "  ['economics','sociology'],\n",
    "  ['css','javascript']]\n",
    "y=['scripting','majors','web']\n",
    "etree_w2v.fit(X,y)\n",
    "test_X=[['perl'],['psychology'],['asp.net']]\n",
    "print(etree_w2v.predict(test_X))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                    Skills\n",
      "0           iTunes Connect\n",
      "1   Mobile Design Paradigm\n",
      "2                     .NET\n",
      "3         Abstract Factory\n",
      "4        Accounting System \n",
      "\n",
      "0                         itunes connect\n",
      "1                 mobile design paradigm\n",
      "2                                   .net\n",
      "3                       abstract factory\n",
      "4                      accounting system\n",
      "5                 accuracy and precision\n",
      "6                 acquisition management\n",
      "7                           activerecord\n",
      "8                               acunetix\n",
      "9                acute coronary syndrome\n",
      "10                 acute pain management\n",
      "11                          ad campaigns\n",
      "12                              adamsoft\n",
      "13                          adaptability\n",
      "14       adapting to changing priorities\n",
      "15                                  adic\n",
      "16      administration and configuration\n",
      "17                       adobe fireworks\n",
      "18                      adobe framemaker\n",
      "19                        adobe freehand\n",
      "20                     adobe illustrator\n",
      "21                        adobe indesign\n",
      "22                       adobe photoshop\n",
      "23                     adolescent health\n",
      "24        advanced features of carbonado\n",
      "25                               adwords\n",
      "26                                   aes\n",
      "27                  aggressive marketing\n",
      "28                                 agile\n",
      "29                     agile development\n",
      "                      ...               \n",
      "1233                                wbts\n",
      "1234                  web analytic tools\n",
      "1235                       web analytics\n",
      "1236                             web api\n",
      "1237                    web applications\n",
      "1238                       web marketing\n",
      "1239                     web page design\n",
      "1240                    web technologies\n",
      "1241                          web trends\n",
      "1242                            webdrive\n",
      "1243                website optimization\n",
      "1244                        websocket.js\n",
      "1245                  what-if simulation\n",
      "1246                           wikipedia\n",
      "1247                             windows\n",
      "1248                             windows\n",
      "1249                          windows os\n",
      "1250                              winscp\n",
      "1251                           wireshark\n",
      "1252                     word processing\n",
      "1253                           wordpress\n",
      "1254               working independently\n",
      "1255                             writing\n",
      "1256                 writing for the web\n",
      "1257               written communication\n",
      "1258                              xcode \n",
      "1259                                 xen\n",
      "1260                               xhtml\n",
      "1261                                 xml\n",
      "1262                             youtube\n",
      "Name: Skills, Length: 1263, dtype: object\n"
     ]
    }
   ],
   "source": [
    "df_skill = pd.read_excel('Skills.xlsx',columns='Skills')\n",
    "print(df_skill.head(),'\\n')\n",
    "skill_series = df_skill.T.squeeze().str.lower()\n",
    "print(skill_series)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[(3, 22), (9, 20), (38, 16), (7, 15), (13, 14), (11, 13), (34, 11), (6, 10), (24, 8), (44, 6), (36, 6), (33, 6), (39, 5), (25, 5), (20, 4), (50, 3), (46, 3), (31, 3), (28, 3), (10, 3), (54, 2), (47, 2), (42, 2), (26, 2), (21, 2), (41, 1), (40, 1), (35, 1), (32, 1), (22, 1), (17, 1), (15, 1), (14, 1), (5, 1), (53, 0), (52, 0), (51, 0), (49, 0), (48, 0), (45, 0), (43, 0), (37, 0), (30, 0), (29, 0), (27, 0), (23, 0), (19, 0), (18, 0), (16, 0), (12, 0), (8, 0), (4, 0), (2, 0), (1, 0), (0, 0)]\n",
      "(9, 20)\n",
      "0     3\n",
      "1     9\n",
      "2    38\n",
      "3     7\n",
      "4    13\n",
      "5    11\n",
      "6    34\n",
      "7     6\n",
      "8    24\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "d = {}\n",
    "import operator\n",
    "for cluster in range(0,num_clusters):\n",
    "    #\n",
    "    # Print the cluster number  \n",
    "    #\n",
    "    # Find all of the words for that cluster number, and print them out\n",
    "    words = []\n",
    "    for key,item in word_centroid_map.items():\n",
    "        if( item == cluster ):\n",
    "            words.append(key)\n",
    "    cluster_series = pd.Series(words)  \n",
    "    temp = pd.Series(list(set(cluster_series)&(set(skill_series))))\n",
    "    d[cluster] = len(temp.values)\n",
    "sorted_d = list(reversed(sorted(d.items(),key=operator.itemgetter(1))))\n",
    "print(sorted_d)\n",
    "print(sorted_d[1])\n",
    "top_ten_skills = []\n",
    "for i in range(0,9):\n",
    "    key,val = sorted_d[i]\n",
    "    top_ten_skills.append(key)\n",
    "top_ten_skills = pd.Series(top_ten_skills)    \n",
    "print(top_ten_skills)    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['light', 'pro', 'macros', 'studios', 'languag', 'rup', 'ms', 'salesforce', 'embarcadero', 'photoshop', 'pivot', 'drupal', 'works', 'simulink', 'powershell', 'tobii', 'mysql', 'familiar', 'bluemix', 'solvertable', 'lucid', 'rstudio', 'captivate', 'google', 'packet', 'axure', 'powerpoint', 'maps', 'visible', 'palisade', 'miscellaneous', 'autodesk', 'pspice', 'dreamweaver', 'explorer', 'arduino', 'modeler', 'assembly', 'itsm', 'excel', 'fiddler', 'files', 'antivirus', 'spss', 'word', 'verilog', 'robot', 'sas', 'precisiontree', 'lynda.com', 'office', 'snagit', 'suites', 'matlab', 'webex', 'lucidchart', 'visio', 'adwords', 'xcode', 'navigator', 'serena', 'arcgis', 'paint', 'proficiency', 'rose', 'parametric', 'proficient', 'stat', 'modeling', 'graphics', 'notes', 'acrobat', 'illustrator', 'prolog', 'visual', 'citrix', 'avaya', 'sqa', 'workbench', 'outlook', 'imaging', 'inventor', 'bloomberg', 'tools', 'draw', 'solver', '@risk', 'ooad', 'precision', 'tableau', 'sql*plus', 'wireshark', 'biweekly', 'skills', 'tbs', 'frontpage', 'studio', 'paradigm', 'autocad', 'bmc', 'media', 'spreadsheet', 'stattools', 'virtualbox', 'proteus', 'minute', 'jigsaw', 'rational', 'suite', 'abode', '365', 'opera', 'creo', 'analyzer', 'charts', 'netscape', 'tables', 'ocaml', 'minitab', 'arena', 'chrome', 'ie', 'lotus', 'salesforce.com', 'adobe', 'flash', 'c++', 'macromedia', 'stata', 'keil', 'python', 'microsoft', 'tracer', 'servicenow', 'docs', 'charles', 'remedy', 'mobizen', 'jmp', 'sharepoint', 'standards', 'consolidation', 'article', 'understanding', 'evolve', 'session', 'audience', 'summary', 'reliability', 'align', 'recommendation', 'functional', 'milestone', 'responsibility', 'verse', 'cases', 'verification', 'feedback', 'iterative', 'input', 'dependency', 'derive', 'clarification', 'followed', 'finalize', 'guideline', 'standardize', 'best', 'simplify', 'actively', 'expectation', 'put', 'communicate', 'traditional', 'convey', 'kyc', 'optimal', 'adherence', 'business', 'assumption', 'wbs', 'sdlc', 'throughout', 'retrospective', 'exposure', 'determine', 'maximum', 'formulate', 'fulfill', 'owner', 'compliant', 'implication', 'matter', 'instruction', 'fit', 'life', 'white', 'strategy', 'refer', 'i.e.', 'governance', 'prioritize', 'cutover', 'assurance', 'offshore', 'processes', 'proposal', 'walkthrough', 'evaluation', 'criterion', 'actual', 'engineered', 'specifications', 'scrum', 'srs', 'identification', 'subject', 'diagrams', 'continuity', 'categorize', 'metrics', 'better', 'pathway', 'sessions', 'context', 'dimension', '⦁', 'analysis', 'phase', 'against', 'detail', 'groom', 'skilled', 'prism', 'qa', 'dictionary', 'shape', 'sow', 'adept', 'smooth', 'knowledge', 'uat', 'strategies', 'upcoming', 'prior', 'actionable', 'delivery', 'engage', 'deadline', 'existing', 'stakeholder', 'brd', 'result', 'rtm', 'deliver', 'convention', 'feasibility', 'strict', 'inception', 'onshore', 'conform', 'structure', 'readiness', 'scorecard', 'departmental', 'results', 'adhere', 'elicit', 'impact', 'super', 'color', 'msrb', 'sat', 'baseline', 'periodic', 'final', 'interpret', 'effort', 'cfo', 'conceptual', 'lifecycle', 'dive', 'directly', 'cio', 'gap', 'publication', 'intelligence', 'gathering', 'charter', 'estimation', 'standardized', 'acceptance', 'practice', 'propose', 'closely', 'participate', 'concise', 'note', 'ccb', 'expedite', 'complex', 'agree', 'consultation', 'facilitate', 'collaborate', 'revise', 'test', 'target', 'definition', 'integral', 'star', 'composer', 'guide', 'judicial', 'jad', 'completion', 'plan', 'supplementary', 'survey', 'carry', 'conducted', 'enhancement', 'direction', 'webinar', 'story', 'ceo', 'e2e', 'hoc', 'spec', 'level', 'expert', 'depth', 'vary', 'identify', 'standard', 'requirement', 'newly', 'present', 'progress', 'mechanic', 'initial', 'reviewed', 'cycle', 'alternative', 'overall', 'coordination', 'draft', 'assess', 'quality', 'methodology', 'planning', 'approach', 'profiling', 'easy', 'assure', 'freddie', 'prepared', 'vision', 'scope', 'rfi', 'accord', 'formulation', 'waterfall', 'sop', 'produce', 'matrix', 'workplace', 'demo', 'deliverable', 'rice', 'meeting', 'method', 'execution', 'repeatable', 'refine', 'fulfil', 'documentation', 'hierarchy', 'objective', 'detailed', 'review', 'diagram', 'specification', 'elicitation', 'demos', 'analyze', 'analyse', 'each', 'stake', 'risk', 'sanity', 'selection', 'translate', 'guidance', 'visibility', 'architectural', 'constraint', 'define', 'team', 'case', 'timeline', 'plans', 'reviews', 'gathered', 'comprehensive', 'streamlined', 'areas', 'met', 'standup', 'flows', 'sme', 'discovery', 'backlog', 'formal', 'scenarios', 'condition', 'consistent', 'ea', 'breakdown', 'ahead', 'gather', 'stlc', 'traceability', 'periodically', 'requests', 'improvement', 'benchmark', 'entire', 'release', 'ready', 'emphasize', 'invest', 'designs', 'transition', 'early', 'technical', 'section', 'roadmap', 'defined', 'smoke', 'regular', 'requirements', 'compose', 'prioritization', 'understand', 'meet', 'conduct', 'sprint', 'metric', 'iteration', 'advice', 'scenario', 'estimate', 'specific', 'study', 'boundary', 'correctness', 'orient', 'goal', 'fully', 'commitment', 'adapt', 'yet', 'attention', 'dedicated', 'analytical', 'challenging', 'motivated', 'communicator', 'influence', 'capable', 'attain', 'technically', 'savvy', 'employment', 'think', 'demonstrate', 'recognition', 'building', 'references', 'recognize', 'positive', 'further', 'great', 'who', 'adaptable', 'adaptability', 'combine', 'forward', 'mind', 'strengthen', 'luther', 'consistently', 'passion', 'volunteering', 'colleague', 'friendly', 'electricity', 'e.', 'very', 'able', 'unique', 'starter', 'aptitude', 'among', 'synthesize', 'onboard', 'interests', 'recipient', 'competent', 'productive', 'preparer', 'provides', 'counseling', 'oral', 'fellow', 'ability', 'leadership', 'fast', 'professional', 'complicated', 'key', 'discipline', 'academic', 'awards', 'prove', 'persuasive', 'round', 'sound', 'du', 'douala', 'advocate', 'highly', 'supervisor', 'crisis', 'seek', 'offer', 'describe', 'attitude', 'accomplishment', 'overview', 'conflict', 'executable', 'while', 'newsletter', 'mentoring', 'supervisory', 'possess', 'cameroon', 'play', 'continued', 'player', 'pursue', 'always', 'creativity', 'independently', 'collaborative', 'qualifications', 'already', 'opportunity', 'learning', 'dedicate', 'challenge', 'practical', 'consensus', 'articulate', 'appreciation', 'give', 'wall', 'consult', 'continue', 'variety', 'making', 'man', 'award', 'presentation', 'thinking', 'brief', 'career', 'involvement', 'choi', 'valuable', 'solid', 'gain', 'interpersonal', 'culture', 'proven', 'classroom', 'term', 'advancement', 'delivered', 'flexibility', 'posses', 'verbal', 'say', '32', 'coo', 'entrepreneurial', 'exceptional', 'accomplish', 'simple', 'excellent', 'succeed', 'tackle', 'effective', 'hardwork', 'face', 'significant', 'innovation', 'flexible', 'ethic', 'motivation', 'diverse', 'position', 'success', 'innovative', 'parent', 'quick', 'navigate', 'stable', 'managerial', 'solve', 'good', 'achievement', 'rapidly', 'creative', 'successful', 'organization', 'excellence', 'towards', 'encourage', 'learner', 'strong', 'skill', 'idea', 'often', 'thorough', 'ideal', 'organizational', 'pressure', 'commit', 'effectively', 'communication', 'coaching', 'outstanding', 'deep', 'adoption', 'personal', 'healthy', 'situation', 'learn', 'enjoy', 'contribute', 'see', 'motivate', 'contribution', 'little', 'pace', 'education', 'extra', 'resident', 'internship', 'willing', 'expand', 'acuman', 'promote', 'teamwork', 'contracting', 'grasp', 'received', 'empower', 'ssl', '\\uf0d8', 'reliable', 'timeout', 'dhcp', 'wire', 'pgp', 'isolate', 'proxy', 'smtp', 'telnet', 'igrp', 'datapower', 'port', 'pop', 'udp', 'virus', 'secured', 'nat', 'ipv6', 't3', 'routers', 'frame', 'juniper', 'switch', 'relay', 'cryptographic', 'retransmission', 'encryption', 'rip', 'pki', 'wins', 'rout', 'dmz', 'rc4', 'bind', 'netware', 'ssh', 'networking', 'distance', 'l2/l3', 'laptop', 'firewall', 'ospf', 'protocols', 'osi', 'printer', 'rsa', 'cryptography', 'https', 'openview', 'tcp', 'certificate', 'socket', 'router', 'bgp', 'voip', 'arp', 'ip', 'ethernet', 'atm', 'authentication', 'cli', 'routing', 'sftp', 'vlan', 'msc', 'catalyst', 'vsphere', 'vpn', 'http', 'dsl', 'wan', 'dossier', 'acl', 'cisco', 'spam', 'ipsec', 'dns', 'certificates', 'lan', 'linksys', 'network', 'forwarding', 'unreliable', 'des', 'password', 'switching', 'layers', 'protocol', 'datagram', 'nfs', 'transport', 'secure', 'securely', 'ids', 'nortel', 'blackberry', 'anti', 'ipv4', 'stp', 'eigrp', 'ftp', 'related', 'sheet', 'like', 'must', 'orders', 'submission', 'extension', 'scheduling', 'read', 'task', 'document', 'corresponding', 'will', 'another', 'into', 'material', '’', 'spread', 'decomposition', 'sensitive', 'trs', 'statement', 'action', 'users', 'would', 'drawing', 'point', '’s', 'sccm', 'move', 'compile', 'drive', 'collect', 'assay', 'schematic', 'equipment', 'for', 'all', 'hundred', 'edit', 'relate', 'etc', 'tool', 'sops', 'managers', 'certain', 'operator', 'same', 'kranthikbheema@gmail.com', 'daily', 'inspection', '\\ue00c', 'mass', 'trial', 'onto', 'successfully', 'monitor', 'printing', 'do', 'edms', 'verify', 'centralize', 'major', 'cards', '10,000', 'other', 'vacation', 'activity', 'response', 'permission', 'cover', 'inventory', 'area', 'remove', 'such', 'up', 'folder', 'also', 'proper', 'register', 'field', 'well', 'operating', 'schedule', 'via', 'receipt', 'connect', 'correspondence', 'exchange', 'floor', 'ran', 'line', 'applicant', 'follow', 'packaging', 'perform', 'receive', 'membership', 'editing', 'assist', 'fedex', 'keeping', 'bpp', 'compilation', 'updating', 'completeness', 'tax', 'updated', 'pre', 'ecr', 'shipping', 'from', 'allocation', 'package', 'physician', 'registration', 'post', 'complete', 'conformance', 'synchronize', 'consolidate', 'medium', 'letter', 'systematic', 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'logging', '45', 'onboarding', 'vendor', 'blackboard', 'content', 'accordance', 'training', 'which', 'so', 'indexing', 'sort', 'style', 'type', 'circumstance', 'contain', 'catch', 'create', 'resource', 'minimize', 'unlock', 'manage', 'ewm', 'help', 'balance', 'across', 'management', 'distribution', 'modified', 'main', 'ghost', 'rare', 'upload', 'template', 'pertinent', 'ship', 'assemble', 'between', 'auditing', 'old', 'audited', 'function', 'many', 'hard', 'bulk', 'pay', 'binder', 'one', 'right', 'basis', 'update', 'available', 'fulfillment', 'merge', 'project', 'expense', 'website', 'user', 'entry', 'mail', 'drill', 'write', 'keep', '100%', 'ownership', 'archival', 'generation', 'collected', 'by', 'with', 'author', 'capture', 'artist', 'shop', 'outgoing', 'performed', 'cq', 'creation', 'time', 'reconcile', 'reference', 'checklist', 'editorial', 'ring', 'valid', 'item', '\\uf06e', 'accurate', 'copy', 'instrument', 'record', 'delete', 'work', 'thermo', 'manager', 'disseminate', 'share', 'required', 'usage', 'execute', 'approve', 'threshold', 'audit', 'transfer', 'remote', 'establish', 'match', 'pc', 'flow', 'assignment', 'an', 'order', 'visa', 'eco', 'within', 'responsible', 'integrity', 'calendar', 'easily', 'example', 'job', 'routine', 'petition', 'aggregate', 'date', 'materials', 'inside', 'bill', 'invoice', 'mrp', 'used', 'consistency', 'locate', 'need', 'storage', 'preparation', 'frequent', 'recent', 'gmp', 'pass', 'comet', 'these', 'provided', 'enforce', 'group', 'searching', 'merchandise', 'policy', 'mis', 'ita', 'weekly', 'allow', 'run', 'archiving', 'portion', 'manual', 'deletion', 'tracking', 'build', 'wachovia', 'approval', 'inclusion', 'classified', 'various', 'form', 'dashboard', 'addition', 'ecybermission', 'over', 'occasion', 'code', 'fiber', 'make', 'wise', 'track', 'invoices', 'fax', 'inspect', 'stage', 'support', 'administrate', 'workgroups', 'operation', 'database', 'panel', 'require', 'procedure', 'list', 'offsite', 'filing', 'process', 'tasks', 'include', 'applicable', 'account', 'freight', 'that', 'be', 'local', 'to', 'renewal', 'registry', 'dependent', 'replace', 'bookkeeping', 'oversaw', 'crud', 'trc', 'upkeep', '120', 'online', 'coordinate', 'original', 'maintenance', 'book', 'revision', 'set', 'layout', 'asset', 'system', 'raw', 'provide', 'rewrite', 'profile', 'created', 'the', 'on', 'inventori', 'handle', 'familiarize', 'developed', 'license', 'map', 'bom', 'current', 'picture', 'own', 'photo', 'underlie', 'manually', 'maintain', 'initiate', 'yearly', 'swift', 'validator', '2000/', 'awt', 'html5', '1.6', 'jdk1.6', 'perl', 'xml', 'jstl', 'jsf', 'theme', 'nodejs', 'j', '1.3', 'frameworks', 'wsad', '2005/2008', 'ilog', 'ejb', 'udb', 'year(s', 'mdb', 'cascading', 'jsps', 'sheets', 'dhtml', 'languages', 'tag', 'joomla', 'gwt', 'applets', 'js', 'appway', 'j2ee', '1.5', 'wireframe', 'json', 'ext', 'css', 'jsp', 'javascript', 'css3', 'uml', 'icefaces', 'responsive', 'jmx', '1.1', 'cgi', 'dom', 'dojo', 'portlets', 'jasper', 'abap', 'ee', 'extjs', 'swings', 'jbuilder', 'rmi', 'faces', 'xhtml', 'page', 'spr', 'bean', 'servlet', 'j2me', 'javabeans', 'webapps', 'csr', 'php', '2.0', 'struts', 'servlets', 'strut', 'tiles', 'java', 'plugin', 'odbc', 'taglibs', 'beans', 'ajax', 'libraries', 'swing', '3.0', 'liferay', '1.2', 'bootstrap', '3.2', 'html', 'jquery', 'd3.js', 'markup', 'xsl', 'ejbs', 'angular', 'angularjs', 'iplanet', 'siteminder', 'novell', 'wily', '4.5', '9i', 'maestro', '10,shell', 'oracle9i', 'macintosh', 'jboss', 'jrockit', 'ubuntu', 'diagnostics', 'el', '6', 'bit', 'websphere', 'centos', '6.x', '1.4', 'red', 'emc', 'dos', '2000/xp', 'hyper', '3.1', '1.0', '8', 'mcafee', 'series', '9.2/10.0', 'balancer', '7.x', 'mqserie', 'f5', 'cics', 'nt', 'linux', 'solaris', 'workstation', 'iis', '6.1/7.0', 'os', 'jprobe', 'mq', 'vms', '5.1', 'symantec', 'flavor', 'apache', 'solaris10', '4.0', '10.3.x', 'scripting', 'ibm', 'windows', 'xp', 'minder', 'sitescope', 'webserver', '6.0', 'boss', 'edition', '5.5', 'netegrity', 'ga', '2.1', 'sunone', 'endeca', '7.1', '95', '10', '9', 'aix', 'me', '10.3/11', '6.2', 'sonic', '4.x', '5.x', 'glassfish', 'ux', '5.0', 'unix', 'vista', 'db2', '5.x/6.x', '7', 'ooa', 'ultra', 'cobol', 'jconsole', 'vmware', 'msie', 'wordpress', '10.0', '9.2.2', '9.2/10.3', 'safari', '7.0', '7.x/8.x', 'alfresco', 'nagios', 'introscope', '6.5', 'mvs', '8.5.5', 'plumtree', 'sun', '8/10', '64', 'rhel', 'sphere', '2.2', 'redhat', '6/7', 'firefox', '11.0', '2000', 'agents', '98', '6.x/7.x', 'mozilla', '4.2', 'oracle10', 'atg', '8.5', '5.1/6.0', '9/10', 'webmethods', 'z', '7.0/8.0', 'dell', 'tomcat', '2000/2003', 'v', 'hat', 'couchbase', 'window', 'eap', '10/8/7', 'platforms', '6.1', '2.x', '8.0', 'informix', 'gateway', 'wiki', 'harvest', 'nexus', 'putty', 'galileo', 'hp', 'mockito', 'subversion', 'puppet', 'jenkin', 'splunk', 'jira', 'safe', 'cygwin', 'selenium', 'patrol', 'bac', 'atlassian', 'jmeter', 'bamboo', 'ide', 'wlst', 'log4j', 'artisan', 'rcp', 'rtc', 'uft', 'cvs', 'soapui', 'starteam', 'tdd', 'alm', 'netbeans', 'dynatrace', '11.5', 'mssql', 'samurai', 'hpqc', 'confluence', 'rally', 'quest', 'clearquest', 'pvcs', 'ci', 'ant', 'tortoise', 'docker', 'cucumber', 'rc', 'clear', 'gradle', 'udeploy', 'plus', 'jaws', 'chef', 'rapid', '12.5', 'adb', 'clearcase', '12.0', 'continuous', 'cruise', 'myeclipse', 'hpalm', 'runner', 'jobs', 'tibco', 'toad', 'intellij', 'nant', 'elementool', 'aqua', 'ems', 'testrail', 'vb', 'cruisecontrol', 'cd', 'devops', 'tfs', 'jython', 'firebug', 'webdriver', 'ruby', 'qtp', 'eclipse', 'vss', 'git', 'perforce', 'loadrunner', 'mantis', 'rail', 'autosys', 'mercury', 'sbm', 'methodologies', 'mtm', 'autonomy', 'bugzilla', 'debug', 'rad', 'junit', 'coldfusion', 'jenkins', 'installer', 'hook', 'pair', 'winscp', 'businessworks', 'ansible', 'cron', 'versioning', 'silk', 'github', 'filezilla', 'svn', 'artifactory', 'sit', 'testng', 'odm', 'winrunner', 'mgmt', 'radar', 'sts', 'maven', 'hudson', 'qc', 'lims', 'injection', 'virtually', 'pega', 'speed', 'mart', 'sim', 'single', 'mulesoft', 'along', 'dow', 'customize', 'coded', 'simultaneously', 'agile', 'extend', 'base', 'gmsec', 'driven', 'gccp', 'gis', 'drm', 'cot', 'customers', 'extensive', 'respectively', 'configurable', '+', 'pipeline', 'synchronization', 'r&d', 'expertise', 'software', 'pioneer', 'reverse', 'integrate', 'feeder', 'orpos', 'tiered', 'usability', 'vob', 'concept', '1.7', 'implement', 'premise', 'compatibility', 'use', 'login', 'develop', 'real', 'reside', 'ppm', 'token', 'utility', 'enhanced', 'object', 'sw', 'cross', 'layer', '3-tier', 'designing', 'embed', 'experience', 'automated', 'multi', 'apigee', 'prototyping', 'coe', 'datacenter', 'center', 'backend', 'specialized', 'complexity', 'queuing', 'nyse', 'core', 'view', 'internationalization', 'ivr', 'ood', 'grouping', 'screen', 'sap', 'retrofit', 'classmate', 'different', 'led', 'coding', 'gui', 'web', 'client-', 'platform', 'everything', 'interfac', 'involve', 'hand', 'functionality', '∙test', 'pilot', 'solution', 'utilize', 'jeppesen', 'emphasis', 'ordination', 'spot', 'architect', 'third', 'geographically', 'scratch', 'scalable', 'browser', 'credential', 'heavy', 'feature', 'whole', 'several', 'bcbs', 'undertaken', 'together', 'proof', 'prototype', 'localization', 'mobility', 'extensively', 'side', 'hana', 'shelf', 'optimized', 'intensive', 'catalog', 'bw', 'have', 'frontend', 'cbs', 'divide', 'capability', 'framework', 'netweaver', 'pacs', 'geographical', 'integrating', 'pos', 'isrweb', 'wallet', 'conceptualize', '3pl', '4', 'ios', 'dream', 'consist', 'addie', 'centralized', 'sync', 'combination', 'applications', 'spoe', 'android', 'tracker', 'entity', '○', 'oriented', 'front', 'oop', 'parallel', 'bridge', 'workflow', 'both', 'class', 'architecture', 'design', 'sdk', 'implemented', 'activation', 'architected', 'vault', 'party', 'leverage', '●', 'later', 'touch', 'built', 'jcl', 'distribute', 'downstream', 'reusable', 'celerkost™', 'common', 'box', 'hybrid', 'active', 'prototyped', 'application', 'cod', 'service', 'modular', 'refactor', 'hec', 'developer', 'experienced', 'development', 'skin', 'end', 'anywhere', 'arm', 'accessibility', 'rich', 'search', 'enterprise', 'multiple', 'disparate', 'standardization', 'proprietary', 'slt', 're', 'kit', 'batch', 'car', 'collaboration', 'edge', 'implementation', 'mid', 's/4', 'hands', 'intel', 'ease', 'appium', 'app', 'relocation', 'cad', 'access', '2', 'driver', 'component', 'product', 'converted', 'authenticate', 'enhance', 'role', 'conjunction', 'commerce', 'polymer', 'isd', 'broadband', 'simulations', 'customized', 'poc', 'sencha', 'automation', 'involved', 'technology', 'custom', 'fpars', 'sites', 'spirent', 'centric', 'azure', 'expose', 'under', 'engine', 'stream', 'api', 'enablement', 'testing', 'oms', 'integration', 'numerous', 'programming', 'interface', 'scm', 'micro', 'exist', 'legacy', 'd.b.a.', \"'s\", 'robust', 'redesign', 'fms', 'plm', 'scale', 'uperform', 'tier', 'mule', 'ecommerce', 'internet', 'ui', 'pm', 'mainframe', '3', 'geospatial', 'powerful', 'structural', 'idms', 'erp', 'client', 'integrated', 'cbt', '12', 'seamless', 'mobile', 'retrieval', 'enable', 'shopping', 'negative']\n"
     ]
    }
   ],
   "source": [
    "skills = []\n",
    "other = []\n",
    "for cluster in range(0,num_clusters):\n",
    "    #\n",
    "    # Print the cluster number  \n",
    "    #\n",
    "    # Find all of the words for that cluster number, and print them out\n",
    "    if top_ten_skills.isin([cluster]).any():\n",
    "        for key,item in word_centroid_map.items():\n",
    "            if(item == cluster):\n",
    "                skills.append(key)\n",
    "    else:\n",
    "        for key,item in word_centroid_map.items():\n",
    "            if(item == cluster):\n",
    "                other.append(key)    \n",
    "                \n",
    "print(skills)                "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['skills' 'skills' 'other']\n",
      "['skills' 'skills' 'other']\n"
     ]
    }
   ],
   "source": [
    "X = [skills,other]\n",
    "y=['skills','other']\n",
    "etree_w2v.fit(X,y)\n",
    "test_X = [['perl'],['ruby'],['university']]\n",
    "print(etree_w2v.predict(test_X))\n",
    "svm_w2v.fit(X,y)\n",
    "print(svm_w2v.predict(test_X))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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