diff --git a/ML/Fake NEWS/Models/Jupyter Notebook/aossie-fake-news-tfidf-nn.ipynb b/ML/Fake NEWS/Models/Jupyter Notebook/aossie-fake-news-tfidf-nn.ipynb index 9648a657..d27a9ea6 100644 --- a/ML/Fake NEWS/Models/Jupyter Notebook/aossie-fake-news-tfidf-nn.ipynb +++ b/ML/Fake NEWS/Models/Jupyter Notebook/aossie-fake-news-tfidf-nn.ipynb @@ -2,67 +2,142 @@ "cells": [ { "cell_type": "code", - "execution_count": 7, + "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Requirement already satisfied: nltk in c:\\users\\visha\\anaconda3\\envs\\pyenv\\lib\\site-packages (3.8.1)\n", - "Requirement already satisfied: tqdm in c:\\users\\visha\\anaconda3\\envs\\pyenv\\lib\\site-packages (4.66.4)\n", - "Requirement already satisfied: keras in c:\\users\\visha\\anaconda3\\envs\\pyenv\\lib\\site-packages (3.3.3)\n", - "Requirement already satisfied: tensorflow in c:\\users\\visha\\anaconda3\\envs\\pyenv\\lib\\site-packages (2.16.1)\n", - 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install nltk tqdm keras tensorflow" + "!pip install nltk tqdm keras tensorflow contractions" ] }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ @@ -92,7 +167,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 10, "metadata": {}, "outputs": [], "source": [ @@ -101,425 +176,19 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 11, "metadata": {}, "outputs": [ { - "data": { - "text/html": [ - "
TfidfVectorizer(max_features=80, stop_words='english', token_pattern='\\\\w{1,}')In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
TfidfVectorizer(max_features=80, stop_words='english', token_pattern='\\\\w{1,}')