diff --git a/foss_regression_3.ipynb b/foss_regression_3.ipynb
new file mode 100644
index 0000000..d8b1275
--- /dev/null
+++ b/foss_regression_3.ipynb
@@ -0,0 +1,541 @@
+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "provenance": [],
+      "toc_visible": true
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "source": [
+        "# Feature Scaling"
+      ],
+      "metadata": {
+        "id": "iHDpbiVxfgfg"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "import numpy as np\n",
+        "import pandas as pd\n",
+        "import matplotlib.pyplot as plt\n",
+        "import seaborn as sns\n",
+        "\n",
+        "#Reading the data for 3 columns\n",
+        "df = pd.read_csv('wines_SPA.csv', usecols=[3, 4, 7])\n",
+        "df.columns=['rating', 'number of reviews', 'price']\n",
+        "\n",
+        "df"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 424
+        },
+        "id": "DzJOENRlfhB3",
+        "outputId": "9cdabf22-1383-4c88-8aca-37d04558ab6a"
+      },
+      "execution_count": 56,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "      rating  number of reviews   price\n",
+              "0        4.9                 58  995.00\n",
+              "1        4.9                 31  313.50\n",
+              "2        4.8               1793  324.95\n",
+              "3        4.8               1705  692.96\n",
+              "4        4.8               1309  778.06\n",
+              "...      ...                ...     ...\n",
+              "7495     4.2                392   19.98\n",
+              "7496     4.2                390   16.76\n",
+              "7497     4.2                390   24.45\n",
+              "7498     4.2                389   64.50\n",
+              "7499     4.2                388   31.63\n",
+              "\n",
+              "[7500 rows x 3 columns]"
+            ],
+            "text/html": [
+              "\n",
+              "  <div id=\"df-5af5c900-4333-4964-9717-e453129ef4ae\" class=\"colab-df-container\">\n",
+              "    <div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
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+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>rating</th>\n",
+              "      <th>number of reviews</th>\n",
+              "      <th>price</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>4.9</td>\n",
+              "      <td>58</td>\n",
+              "      <td>995.00</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>4.9</td>\n",
+              "      <td>31</td>\n",
+              "      <td>313.50</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>4.8</td>\n",
+              "      <td>1793</td>\n",
+              "      <td>324.95</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>4.8</td>\n",
+              "      <td>1705</td>\n",
+              "      <td>692.96</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>4.8</td>\n",
+              "      <td>1309</td>\n",
+              "      <td>778.06</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>...</th>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>7495</th>\n",
+              "      <td>4.2</td>\n",
+              "      <td>392</td>\n",
+              "      <td>19.98</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>7496</th>\n",
+              "      <td>4.2</td>\n",
+              "      <td>390</td>\n",
+              "      <td>16.76</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>7497</th>\n",
+              "      <td>4.2</td>\n",
+              "      <td>390</td>\n",
+              "      <td>24.45</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>7498</th>\n",
+              "      <td>4.2</td>\n",
+              "      <td>389</td>\n",
+              "      <td>64.50</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>7499</th>\n",
+              "      <td>4.2</td>\n",
+              "      <td>388</td>\n",
+              "      <td>31.63</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "<p>7500 rows × 3 columns</p>\n",
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+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
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+              "\n",
+              "    [theme=dark] .colab-df-convert:hover {\n",
+              "      background-color: #434B5C;\n",
+              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "      fill: #FFFFFF;\n",
+              "    }\n",
+              "  </style>\n",
+              "\n",
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+              "      const buttonEl =\n",
+              "        document.querySelector('#df-5af5c900-4333-4964-9717-e453129ef4ae button.colab-df-convert');\n",
+              "      buttonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "      async function convertToInteractive(key) {\n",
+              "        const element = document.querySelector('#df-5af5c900-4333-4964-9717-e453129ef4ae');\n",
+              "        const dataTable =\n",
+              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                    [key], {});\n",
+              "        if (!dataTable) return;\n",
+              "\n",
+              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "          + ' to learn more about interactive tables.';\n",
+              "        element.innerHTML = '';\n",
+              "        dataTable['output_type'] = 'display_data';\n",
+              "        await google.colab.output.renderOutput(dataTable, element);\n",
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+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart-complete:disabled,\n",
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+              "    background-color: var(--disabled-bg-color);\n",
+              "    fill: var(--disabled-fill-color);\n",
+              "    box-shadow: none;\n",
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+              "\n",
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+              "      const quickchartButtonEl =\n",
+              "        document.querySelector('#' + key + ' button');\n",
+              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
+              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
+              "      try {\n",
+              "        const charts = await google.colab.kernel.invokeFunction(\n",
+              "            'suggestCharts', [key], {});\n",
+              "      } catch (error) {\n",
+              "        console.error('Error during call to suggestCharts:', error);\n",
+              "      }\n",
+              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+              "    }\n",
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+              "      quickchartButtonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "    })();\n",
+              "  </script>\n",
+              "</div>\n",
+              "\n",
+              "  <div id=\"id_dc4854bf-8b5f-4817-a4d7-37c4250c689e\">\n",
+              "    <style>\n",
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+              "      }\n",
+              "\n",
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+              "        fill: #174EA6;\n",
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+              "\n",
+              "      [theme=dark] .colab-df-generate {\n",
+              "        background-color: #3B4455;\n",
+              "        fill: #D2E3FC;\n",
+              "      }\n",
+              "\n",
+              "      [theme=dark] .colab-df-generate:hover {\n",
+              "        background-color: #434B5C;\n",
+              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
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+              "    </style>\n",
+              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df')\"\n",
+              "            title=\"Generate code using this dataframe.\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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+              "\n",
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+              "  </div>\n"
+            ],
+            "application/vnd.google.colaboratory.intrinsic+json": {
+              "type": "dataframe",
+              "variable_name": "df",
+              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 7500,\n  \"fields\": [\n    {\n      \"column\": \"rating\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.1180290345746442,\n        \"min\": 4.2,\n        \"max\": 4.9,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          4.8,\n          4.4,\n          4.9\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"number of reviews\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 723,\n        \"min\": 25,\n        \"max\": 32624,\n        \"num_unique_values\": 817,\n        \"samples\": [\n          115,\n          177,\n          2144\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"price\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 150.35667645268242,\n        \"min\": 4.99,\n        \"max\": 3119.08,\n        \"num_unique_values\": 1292,\n        \"samples\": [\n          168.0,\n          190.0,\n          28.7315367295517\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
+            }
+          },
+          "metadata": {},
+          "execution_count": 56
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "#here, i have plotted the graph for the taken three columns\n",
+        "number_of_reviews = df['num_reviews']\n",
+        "price = df['price']\n",
+        "rating = df['rating']\n",
+        "\n",
+        "plt.figure(figsize=(9, 4))\n",
+        "scatter = plt.scatter(rating, price, c=number_of_reviews, cmap='viridis')\n",
+        "plt.xlabel('rating')\n",
+        "plt.ylabel('Price')\n",
+        "plt.title('Wine data before feature scaling')\n",
+        "plt.legend()\n",
+        "plt.grid(True)\n",
+        "plt.show()"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 427
+        },
+        "id": "uuQxMfcRic_4",
+        "outputId": "c4d17657-09be-44ea-8b9a-73dbea7821ea"
+      },
+      "execution_count": 48,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "WARNING:matplotlib.legend:No artists with labels found to put in legend.  Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n"
+          ]
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 900x400 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {}
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "# implementing minmax scaling method of feature scaling for the given columns\n",
+        "from sklearn.preprocessing import MinMaxScaler\n",
+        "\n",
+        "scaler = MinMaxScaler()\n",
+        "number_of_reviews_scaled = scaler.fit_transform(number_of_reviews)\n",
+        "price_scaled = scaler.fit_transform(price)\n",
+        "rating_scaled = scaler.fit_transform(rating)\n",
+        "\n",
+        "plt.figure(figsize=(9, 4))\n",
+        "plt.scatter(rating_scaled, price_scaled, c=number_of_reviews_scaled, cmap='viridis', label='Number of reviews')\n",
+        "plt.xlabel('rating')\n",
+        "plt.ylabel('price')\n",
+        "plt.title('Wine data after feature scaling(price, rating, number of reviews)')\n",
+        "plt.legend()\n",
+        "plt.grid(True)\n",
+        "plt.show()"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 410
+        },
+        "id": "qyEsbGM9v-W9",
+        "outputId": "31c334af-f46f-4fb5-fd7e-562e63e829fb"
+      },
+      "execution_count": 55,
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 900x400 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {}
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [],
+      "metadata": {
+        "id": "A7BXRJVm8ArS"
+      },
+      "execution_count": null,
+      "outputs": []
+    }
+  ]
+}
\ No newline at end of file