Product_Recommendation_System_Project.ipynb

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    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/SACHINSIROHI47/DataScience_with_Python_Programming_Project/blob/main/Product_Recommendation_System_Project.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **Product Recommendation System for E-Commerce Website**"
      ],
      "metadata": {
        "id": "ZUDPU0XcOH2O"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "A recommendation engine in Python is a software tool that uses machine learning to suggest items to a user based on their **interests, preferences,Rating, and behavior**. Recommendation engines are used by many companies, including **Netflix, Amazon, YouTube, and Spotify**, to improve user experience and drive revenue"
      ],
      "metadata": {
        "id": "BnMtC6oqOPjJ"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **Import Library**"
      ],
      "metadata": {
        "id": "7LP-oa-hQJEG"
      }
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    {
      "cell_type": "code",
      "execution_count": 1,
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      "outputs": [],
      "source": [
        "#import Library\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "\n",
        "plt.style.use('ggplot')\n",
        "\n",
        "import sklearn\n",
        "from sklearn.decomposition import TruncatedSVD"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **Load Dataset**"
      ],
      "metadata": {
        "id": "vTGbiyUaQRUA"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import files\n",
        "uploaded = files.upload()"
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          "height": 73
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        "outputId": "2e37e7ca-811d-4f43-cea7-d961bdd005ca"
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              "      Upload widget is only available when the cell has been executed in the\n",
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              "// you may not use this file except in compliance with the License.\n",
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              "//      http://www.apache.org/licenses/LICENSE-2.0\n",
              "//\n",
              "// Unless required by applicable law or agreed to in writing, software\n",
              "// distributed under the License is distributed on an \"AS IS\" BASIS,\n",
              "// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
              "// See the License for the specific language governing permissions and\n",
              "// limitations under the License.\n",
              "\n",
              "/**\n",
              " * @fileoverview Helpers for google.colab Python module.\n",
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              "\n",
              "// This is roughly an async generator (not supported in the browser yet),\n",
              "// where there are multiple asynchronous steps and the Python side is going\n",
              "// to poll for completion of each step.\n",
              "// This uses a Promise to block the python side on completion of each step,\n",
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              "\n",
              "    // Use a chunked sending to avoid message size limits. See b/62115660.\n",
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              "scope.google = scope.google || {};\n",
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        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Saving ratings_Beauty_Product.csv to ratings_Beauty_Product.csv\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "rating=pd.read_csv('ratings_Beauty_Product.csv')\n",
        "rating.head()"
      ],
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        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
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        "id": "kEWkO8WPVqQk",
        "outputId": "098911f0-d0bb-43b7-cf77-19b6112d5219"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "           UserId   ProductId  Rating   Timestamp\n",
              "0  A39HTATAQ9V7YF  0205616461     5.0  1369699200\n",
              "1  A3JM6GV9MNOF9X  0558925278     3.0  1355443200\n",
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              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
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              "type": "dataframe",
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    {
      "cell_type": "code",
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        "rating.isnull().sum()"
      ],
      "metadata": {
        "colab": {
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          "height": 209
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        "id": "ZB6hZDyXWQWm",
        "outputId": "a7832ebe-bdec-4896-a07f-9e9430b62ce9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "UserId       0\n",
              "ProductId    0\n",
              "Rating       0\n",
              "Timestamp    0\n",
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    {
      "cell_type": "code",
      "source": [
        "amazon_rating=rating.dropna()\n",
        "amazon_rating.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "TL4fUZiOWCLw",
        "outputId": "0a616f74-5f1f-4223-adf3-9205720d8149"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "           UserId   ProductId  Rating   Timestamp\n",
              "0  A39HTATAQ9V7YF  0205616461     5.0  1369699200\n",
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            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "amazon_rating"
            }
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#groupby rating by productid\n",
        "rating_count = pd.DataFrame(amazon_rating.groupby('ProductId')['Rating'].count())\n",
        "most_rating=rating_count.sort_values('Rating', ascending=False).head(10)\n",
        "most_rating.head()\n",
        "#"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 237
        },
        "id": "ePiTyjbVWf-W",
        "outputId": "e8008f58-09da-4f0b-c173-d6c6c09f8839"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            Rating\n",
              "ProductId         \n",
              "B001MA0QY2    7533\n",
              "B0009V1YR8    2869\n",
              "B0043OYFKU    2477\n",
              "B0000YUXI0    2143\n",
              "B003V265QW    2088"
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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",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-e814b5a6-2793-438e-b9ca-e4b969f87740 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-e814b5a6-2793-438e-b9ca-e4b969f87740');\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",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-7c9fa328-9653-4134-b5d9-d026e34f4323\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-7c9fa328-9653-4134-b5d9-d026e34f4323')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      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",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-7c9fa328-9653-4134-b5d9-d026e34f4323 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"#\",\n  \"rows\": 5,\n  \"fields\": [\n    {\n      \"column\": \"ProductId\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          \"B0009V1YR8\",\n          \"B003V265QW\",\n          \"B0043OYFKU\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Rating\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2319,\n        \"min\": 2088,\n        \"max\": 7533,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          2869,\n          2088,\n          2477\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#plotting most_rating data\n",
        "fig=plt.figure(figsize=(10,3))\n",
        "most_rating.plot(kind='bar')\n",
        "plt.xlabel('ProductId')\n",
        "plt.ylabel('Rating')\n",
        "plt.title('Most Rating Product')\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 578
        },
        "id": "OJyovFFJW1Oc",
        "outputId": "e650bc19-5720-4857-d089-c4230cfab208"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x300 with 0 Axes>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        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)"
      ],
      "metadata": {
        "id": "K4hQMbrRYlwD"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **Model Based Collaborative Filtering System**"
      ],
      "metadata": {
        "id": "9ijANr68Y26g"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#subset of rating\n",
        "amazon_rating1=amazon_rating.head(10000)\n",
        "amazon_rating1.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZclqSJQoYh-K",
        "outputId": "8246fd71-c457-4d19-a829-8664f979808a"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(10000, 4)"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#show pivot tables of ratings\n",
        "ratingMatrix=amazon_rating1.pivot_table(index=['UserId'],columns=['ProductId'],values='Rating',fill_value=0)\n",
        "ratingMatrix.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 286
        },
        "id": "MjcA8hpZZRnQ",
        "outputId": "57de1c67-20ca-4a4c-d09d-e68c1c31f1b9"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "ProductId              0205616461  0558925278  0733001998  0737104473  \\\n",
              "UserId                                                                  \n",
              "A00205921JHJK5X9LNP42         0.0         0.0         0.0         0.0   \n",
              "A024581134CV80ZBLIZTZ         0.0         0.0         0.0         0.0   \n",
              "A03056581JJIOL5FSKJY7         0.0         0.0         0.0         0.0   \n",
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            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "ratingMatrix"
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          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#shape of rating\n",
        "ratingMatrix.shape"
      ],
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        },
        "id": "lWhQaSpPaWbD",
        "outputId": "7c082439-5598-4480-cb9d-6a0083dd69d0"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(9697, 886)"
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          },
          "metadata": {},
          "execution_count": 9
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      ]
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    {
      "cell_type": "code",
      "source": [
        "#Transposing the matrix\n",
        "X=ratingMatrix.T\n",
        "X.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 286
        },
        "id": "lD0E4dv2afO9",
        "outputId": "26f8da44-3aed-449a-8259-02ec12847bd3"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
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              "\n",
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            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "X"
            }
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "X.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "heU1i8lnarc3",
        "outputId": "057cb083-af98-4ef6-e482-6175a9f28d64"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(886, 9697)"
            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#unique product\n",
        "X1=X"
      ],
      "metadata": {
        "id": "BU6GkmM9avdK"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
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)"
      ],
      "metadata": {
        "id": "7OnRwvoichUD"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#Decomposing the matrix\n",
        "import sklearn\n",
        "from sklearn.decomposition import TruncatedSVD\n",
        "\n",
        "SVD=TruncatedSVD(n_components=10)\n",
        "decomposed_matrix=SVD.fit_transform(X)\n",
        "decomposed_matrix.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Suy9z9RNa4do",
        "outputId": "75283df0-f60f-4ade-c996-0f49b1e687bc"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(886, 10)"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "decomposed_matrix"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HnOnwbaBc8Qd",
        "outputId": "3298e2d6-9050-4680-cc05-43af774430e3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[-6.05718169e-16,  3.67623783e-14, -3.42949288e-14, ...,\n",
              "         9.68880415e-13, -7.59445161e-13, -1.96482289e-12],\n",
              "       [ 4.75640932e-14,  1.48481377e-12, -7.36053630e-14, ...,\n",
              "         1.45924244e-11, -2.26239489e-11, -6.93379646e-11],\n",
              "       [ 2.16887762e-16,  5.82301993e-15,  3.46838935e-15, ...,\n",
              "         3.49370089e-14, -5.85464259e-14, -2.31132560e-14],\n",
              "       ...,\n",
              "       [ 3.34750003e-06,  2.27951253e-01, -1.04084890e-02, ...,\n",
              "        -3.76957501e-03, -5.98145337e-05, -4.90195615e-02],\n",
              "       [ 1.50567751e-06,  8.94551004e-04,  1.15903289e-05, ...,\n",
              "         5.48185550e-04, -1.33781840e-03, -3.13737245e-03],\n",
              "       [ 2.57507909e-04,  4.18283171e-01,  3.54585287e-01, ...,\n",
              "        -2.20919333e-02,  6.27159430e-02, -1.07169479e-01]])"
            ]
          },
          "metadata": {},
          "execution_count": 37
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Correlation Matrix\n",
        "import numpy as np\n",
        "correlation_matrix=np.corrcoef(decomposed_matrix)\n",
        "correlation_matrix.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WYiLt6-hbIMV",
        "outputId": "b4c8c55a-639b-465e-e1f3-cb3c7caa8677"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(886, 886)"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "correlation_matrix"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Vrca6QgXdAFm",
        "outputId": "ba334137-d936-4f33-93ed-b760c545658e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[1.        , 0.97007693, 0.67371409, ..., 0.27118195, 0.63623024,\n",
              "        0.16511905],\n",
              "       [0.97007693, 1.        , 0.57936105, ..., 0.32197041, 0.69628721,\n",
              "        0.30241552],\n",
              "       [0.67371409, 0.57936105, 1.        , ..., 0.17686438, 0.66473725,\n",
              "        0.20686348],\n",
              "       ...,\n",
              "       [0.27118195, 0.32197041, 0.17686438, ..., 1.        , 0.30172583,\n",
              "        0.21939084],\n",
              "       [0.63623024, 0.69628721, 0.66473725, ..., 0.30172583, 1.        ,\n",
              "        0.71773046],\n",
              "       [0.16511905, 0.30241552, 0.20686348, ..., 0.21939084, 0.71773046,\n",
              "        1.        ]])"
            ]
          },
          "metadata": {},
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Assuming the cusotmer buys productid randomly"
      ],
      "metadata": {
        "id": "Nw7L2Zn6eCIq"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "X.index[99]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 36
        },
        "id": "RKKMex5_d9Sg",
        "outputId": "09dc9173-964d-4a6e-d177-2097c22483c8"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'6117036094'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "index_value='6117036094'\n",
        "productName=list(X.index)\n",
        "productID=productName.index(index_value)\n",
        "productID\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "A8jugCIveQRq",
        "outputId": "5b673394-7014-4372-e226-3fe0cc53307a"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "99"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Correlation for all item purchase by user\n",
        "correlation_productID=correlation_matrix[productID]\n",
        "correlation_productID.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hBJhMfryeo66",
        "outputId": "084f074f-1f42-48c9-ef8a-94a1d6d18cc2"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(886,)"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Recommending top 10 highly correlated product\n",
        "Recommend=list(X.index[correlation_productID>0.90])\n",
        "Recommend.remove(index_value)\n",
        "Recommend[0:10]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uEEYW2QBe2I5",
        "outputId": "d291408d-9fe1-4eae-a0ed-80e1b9cd273d"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['1304351475',\n",
              " '3222000565',\n",
              " '4057362797',\n",
              " '4057363823',\n",
              " '6040652705',\n",
              " '8072222120',\n",
              " '8096398741',\n",
              " '8982641262',\n",
              " '9502737628',\n",
              " '957696718X']"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Recommanded based on Textual Clustering. Usert Item Purchase History**"
      ],
      "metadata": {
        "id": "W2hKi4MSTSfE"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#import machine learning library\n",
        "from sklearn.feature_extraction.text import TfidfVectorizer,CountVectorizer\n",
        "from sklearn.cluster import KMeans\n",
        "from sklearn.neighbors import NearestNeighbors\n",
        "from sklearn.metrics import adjusted_rand_score\n"
      ],
      "metadata": {
        "id": "i9WR-CShfIjI"
      },
      "execution_count": 17,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "#Item Based Recommendation based on product description"
      ],
      "metadata": {
        "id": "ghsh4iqsULe2"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import files\n",
        "uploaded = files.upload()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 73
        },
        "id": "C1yToeYAUHFs",
        "outputId": "cbaca6f7-d9f9-46cf-a139-c9376100249d"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "\n",
              "     <input type=\"file\" id=\"files-924b28c1-83e6-46fd-9a90-710de365680b\" name=\"files[]\" multiple disabled\n",
              "        style=\"border:none\" />\n",
              "     <output id=\"result-924b28c1-83e6-46fd-9a90-710de365680b\">\n",
              "      Upload widget is only available when the cell has been executed in the\n",
              "      current browser session. Please rerun this cell to enable.\n",
              "      </output>\n",
              "      <script>// Copyright 2017 Google LLC\n",
              "//\n",
              "// Licensed under the Apache License, Version 2.0 (the \"License\");\n",
              "// you may not use this file except in compliance with the License.\n",
              "// You may obtain a copy of the License at\n",
              "//\n",
              "//      http://www.apache.org/licenses/LICENSE-2.0\n",
              "//\n",
              "// Unless required by applicable law or agreed to in writing, software\n",
              "// distributed under the License is distributed on an \"AS IS\" BASIS,\n",
              "// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
              "// See the License for the specific language governing permissions and\n",
              "// limitations under the License.\n",
              "\n",
              "/**\n",
              " * @fileoverview Helpers for google.colab Python module.\n",
              " */\n",
              "(function(scope) {\n",
              "function span(text, styleAttributes = {}) {\n",
              "  const element = document.createElement('span');\n",
              "  element.textContent = text;\n",
              "  for (const key of Object.keys(styleAttributes)) {\n",
              "    element.style[key] = styleAttributes[key];\n",
              "  }\n",
              "  return element;\n",
              "}\n",
              "\n",
              "// Max number of bytes which will be uploaded at a time.\n",
              "const MAX_PAYLOAD_SIZE = 100 * 1024;\n",
              "\n",
              "function _uploadFiles(inputId, outputId) {\n",
              "  const steps = uploadFilesStep(inputId, outputId);\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  // Cache steps on the outputElement to make it available for the next call\n",
              "  // to uploadFilesContinue from Python.\n",
              "  outputElement.steps = steps;\n",
              "\n",
              "  return _uploadFilesContinue(outputId);\n",
              "}\n",
              "\n",
              "// This is roughly an async generator (not supported in the browser yet),\n",
              "// where there are multiple asynchronous steps and the Python side is going\n",
              "// to poll for completion of each step.\n",
              "// This uses a Promise to block the python side on completion of each step,\n",
              "// then passes the result of the previous step as the input to the next step.\n",
              "function _uploadFilesContinue(outputId) {\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  const steps = outputElement.steps;\n",
              "\n",
              "  const next = steps.next(outputElement.lastPromiseValue);\n",
              "  return Promise.resolve(next.value.promise).then((value) => {\n",
              "    // Cache the last promise value to make it available to the next\n",
              "    // step of the generator.\n",
              "    outputElement.lastPromiseValue = value;\n",
              "    return next.value.response;\n",
              "  });\n",
              "}\n",
              "\n",
              "/**\n",
              " * Generator function which is called between each async step of the upload\n",
              " * process.\n",
              " * @param {string} inputId Element ID of the input file picker element.\n",
              " * @param {string} outputId Element ID of the output display.\n",
              " * @return {!Iterable<!Object>} Iterable of next steps.\n",
              " */\n",
              "function* uploadFilesStep(inputId, outputId) {\n",
              "  const inputElement = document.getElementById(inputId);\n",
              "  inputElement.disabled = false;\n",
              "\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  outputElement.innerHTML = '';\n",
              "\n",
              "  const pickedPromise = new Promise((resolve) => {\n",
              "    inputElement.addEventListener('change', (e) => {\n",
              "      resolve(e.target.files);\n",
              "    });\n",
              "  });\n",
              "\n",
              "  const cancel = document.createElement('button');\n",
              "  inputElement.parentElement.appendChild(cancel);\n",
              "  cancel.textContent = 'Cancel upload';\n",
              "  const cancelPromise = new Promise((resolve) => {\n",
              "    cancel.onclick = () => {\n",
              "      resolve(null);\n",
              "    };\n",
              "  });\n",
              "\n",
              "  // Wait for the user to pick the files.\n",
              "  const files = yield {\n",
              "    promise: Promise.race([pickedPromise, cancelPromise]),\n",
              "    response: {\n",
              "      action: 'starting',\n",
              "    }\n",
              "  };\n",
              "\n",
              "  cancel.remove();\n",
              "\n",
              "  // Disable the input element since further picks are not allowed.\n",
              "  inputElement.disabled = true;\n",
              "\n",
              "  if (!files) {\n",
              "    return {\n",
              "      response: {\n",
              "        action: 'complete',\n",
              "      }\n",
              "    };\n",
              "  }\n",
              "\n",
              "  for (const file of files) {\n",
              "    const li = document.createElement('li');\n",
              "    li.append(span(file.name, {fontWeight: 'bold'}));\n",
              "    li.append(span(\n",
              "        `(${file.type || 'n/a'}) - ${file.size} bytes, ` +\n",
              "        `last modified: ${\n",
              "            file.lastModifiedDate ? file.lastModifiedDate.toLocaleDateString() :\n",
              "                                    'n/a'} - `));\n",
              "    const percent = span('0% done');\n",
              "    li.appendChild(percent);\n",
              "\n",
              "    outputElement.appendChild(li);\n",
              "\n",
              "    const fileDataPromise = new Promise((resolve) => {\n",
              "      const reader = new FileReader();\n",
              "      reader.onload = (e) => {\n",
              "        resolve(e.target.result);\n",
              "      };\n",
              "      reader.readAsArrayBuffer(file);\n",
              "    });\n",
              "    // Wait for the data to be ready.\n",
              "    let fileData = yield {\n",
              "      promise: fileDataPromise,\n",
              "      response: {\n",
              "        action: 'continue',\n",
              "      }\n",
              "    };\n",
              "\n",
              "    // Use a chunked sending to avoid message size limits. See b/62115660.\n",
              "    let position = 0;\n",
              "    do {\n",
              "      const length = Math.min(fileData.byteLength - position, MAX_PAYLOAD_SIZE);\n",
              "      const chunk = new Uint8Array(fileData, position, length);\n",
              "      position += length;\n",
              "\n",
              "      const base64 = btoa(String.fromCharCode.apply(null, chunk));\n",
              "      yield {\n",
              "        response: {\n",
              "          action: 'append',\n",
              "          file: file.name,\n",
              "          data: base64,\n",
              "        },\n",
              "      };\n",
              "\n",
              "      let percentDone = fileData.byteLength === 0 ?\n",
              "          100 :\n",
              "          Math.round((position / fileData.byteLength) * 100);\n",
              "      percent.textContent = `${percentDone}% done`;\n",
              "\n",
              "    } while (position < fileData.byteLength);\n",
              "  }\n",
              "\n",
              "  // All done.\n",
              "  yield {\n",
              "    response: {\n",
              "      action: 'complete',\n",
              "    }\n",
              "  };\n",
              "}\n",
              "\n",
              "scope.google = scope.google || {};\n",
              "scope.google.colab = scope.google.colab || {};\n",
              "scope.google.colab._files = {\n",
              "  _uploadFiles,\n",
              "  _uploadFilesContinue,\n",
              "};\n",
              "})(self);\n",
              "</script> "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Saving product_descriptions.csv to product_descriptions.csv\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "prod_desc=pd.read_csv('product_descriptions.csv')\n",
        "prod_desc.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "edbkTiT-cbH8",
        "outputId": "ec1edf81-ed8e-426e-b757-bac5f764ae35"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   product_uid                                product_description\n",
              "0       100001  Not only do angles make joints stronger, they ...\n",
              "1       100002  BEHR Premium Textured DECKOVER is an innovativ...\n",
              "2       100003  Classic architecture meets contemporary design...\n",
              "3       100004  The Grape Solar 265-Watt Polycrystalline PV So...\n",
              "4       100005  Update your bathroom with the Delta Vero Singl..."
            ],
            "text/html": [
              "\n",
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              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
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              "    }\n",
              "\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>product_uid</th>\n",
              "      <th>product_description</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>100001</td>\n",
              "      <td>Not only do angles make joints stronger, they ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>100002</td>\n",
              "      <td>BEHR Premium Textured DECKOVER is an innovativ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>100003</td>\n",
              "      <td>Classic architecture meets contemporary design...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>100004</td>\n",
              "      <td>The Grape Solar 265-Watt Polycrystalline PV So...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>100005</td>\n",
              "      <td>Update your bathroom with the Delta Vero Singl...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-8586f6e6-3ffb-4cde-93e9-ec339cc71755')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\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",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-8586f6e6-3ffb-4cde-93e9-ec339cc71755 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-8586f6e6-3ffb-4cde-93e9-ec339cc71755');\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",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-0958fc55-b7b6-4438-975a-f9f1019e60d3\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-0958fc55-b7b6-4438-975a-f9f1019e60d3')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      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",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-0958fc55-b7b6-4438-975a-f9f1019e60d3 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "prod_desc"
            }
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Missing values\n",
        "prod_desc.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 146
        },
        "id": "mFGqsSHPc9KW",
        "outputId": "68d48bfa-250c-4d63-8d7d-0bbd6b17d35a"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "product_uid            0\n",
              "product_description    0\n",
              "dtype: int64"
            ],
            "text/html": [
              "<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",
              "    }\n",
              "\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>0</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>product_uid</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>product_description</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div><br><label><b>dtype:</b> int64</label>"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Feature extraction\n",
        "vectorizer=TfidfVectorizer(stop_words='english')\n",
        "X=vectorizer.fit_transform(prod_desc['product_description'])\n",
        "X"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "tujeTUhGgjzi",
        "outputId": "195ef1e4-18cd-41a8-c6e2-aeacf77c872c"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<124428x268559 sparse matrix of type '<class 'numpy.float64'>'\n",
              "\twith 8256891 stored elements in Compressed Sparse Row format>"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#fitting k-means\n",
        "true_k=10\n",
        "model=KMeans(n_clusters=true_k,init='k-means++',max_iter=100,n_init=1)\n",
        "# model.fit(X)"
      ],
      "metadata": {
        "id": "1vLN1LLwg7h-"
      },
      "execution_count": 27,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#predicting and visualise\n",
        "y_pred=model.fit_predict(X)\n",
        "plt.plot(y_pred,'.')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 430
        },
        "id": "o28zadd4hqv6",
        "outputId": "5aa61f85-00e6-4357-ddc3-0b67a5f420f4"
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#optimal cluster\n",
        "tk=10\n",
        "model=KMeans(n_clusters=true_k,init='k-means++',max_iter=100,n_init=1)\n",
        "y_pred=model.fit(X)\n",
        "print(\"Top terms per cluster:\")\n",
        "order_centroids=model.cluster_centers_.argsort()[:,::-1]\n",
        "terms=vectorizer.get_feature_names_out()\n",
        "for i in range(true_k):\n",
        "  print(\"Cluster %d:\" %i)\n",
        "  for ind in order_centroids[i,:10]:\n",
        "    print(' %s' %terms[ind])\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Ld6yc3g9j2QF",
        "outputId": "4cd4379d-cf1e-4d3e-a7fb-d39a0afc0c43"
      },
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Top terms per cluster:\n",
            "Cluster 0:\n",
            " easy\n",
            " ft\n",
            " use\n",
            " wood\n",
            " home\n",
            " wall\n",
            " design\n",
            " steel\n",
            " durable\n",
            " resistant\n",
            "Cluster 1:\n",
            " fan\n",
            " oven\n",
            " cooking\n",
            " cu\n",
            " freezer\n",
            " ceiling\n",
            " ft\n",
            " refrigerator\n",
            " food\n",
            " temperature\n",
            "Cluster 2:\n",
            " grade\n",
            " nuts\n",
            " laminate\n",
            " proposition\n",
            " residents\n",
            " nbsp\n",
            " 65\n",
            " california\n",
            " wood\n",
            " screws\n",
            "Cluster 3:\n",
            " tile\n",
            " indoor\n",
            " residential\n",
            " recommended\n",
            " thinset\n",
            " frost\n",
            " piece\n",
            " pieces\n",
            " wall\n",
            " commercial\n",
            "Cluster 4:\n",
            " door\n",
            " doors\n",
            " glass\n",
            " shower\n",
            " panel\n",
            " adjustable\n",
            " steel\n",
            " hinges\n",
            " cabinet\n",
            " hardware\n",
            "Cluster 5:\n",
            " light\n",
            " energy\n",
            " bulb\n",
            " watt\n",
            " led\n",
            " lighting\n",
            " hours\n",
            " bulbs\n",
            " incandescent\n",
            " white\n",
            "Cluster 6:\n",
            " vanity\n",
            " glass\n",
            " hardware\n",
            " finish\n",
            " collection\n",
            " cabinet\n",
            " light\n",
            " nickel\n",
            " included\n",
            " fixture\n",
            "Cluster 7:\n",
            " shower\n",
            " water\n",
            " faucet\n",
            " sink\n",
            " valve\n",
            " drain\n",
            " handle\n",
            " tub\n",
            " brass\n",
            " design\n",
            "Cluster 8:\n",
            " steel\n",
            " power\n",
            " use\n",
            " air\n",
            " volt\n",
            " tool\n",
            " cutting\n",
            " blade\n",
            " pipe\n",
            " designed\n",
            "Cluster 9:\n",
            " paint\n",
            " vary\n",
            " rug\n",
            " colors\n",
            " color\n",
            " gloss\n",
            " slightly\n",
            " wood\n",
            " mn\n",
            " ri\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#predicting cluster based on key search\n",
        "def disp_recomd(prod):\n",
        "  Y=vectorizer.transform([prod])\n",
        "  prediction=model.predict(Y)\n",
        "  i=prediction[0]\n",
        "  for ind in order_centroids[i,:10]:\n",
        "    print(' %s' %terms[ind])"
      ],
      "metadata": {
        "id": "fSucTl6Wlu9o"
      },
      "execution_count": 43,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#Keyword - cutting tool\n",
        "disp_recomd('cutting tool')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "FvytPknmmDup",
        "outputId": "d5321576-6fbb-47d4-f043-aae4659f59e8"
      },
      "execution_count": 44,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            " steel\n",
            " power\n",
            " use\n",
            " air\n",
            " volt\n",
            " tool\n",
            " cutting\n",
            " blade\n",
            " pipe\n",
            " designed\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Keyword - spray paint\n",
        "disp_recomd('spray paint')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CfLPelnRmKF3",
        "outputId": "62f1c030-755e-48d2-ffcd-9664af72810b"
      },
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            " paint\n",
            " vary\n",
            " rug\n",
            " colors\n",
            " color\n",
            " gloss\n",
            " slightly\n",
            " wood\n",
            " mn\n",
            " ri\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Keyword- steel drill\n",
        "disp_recomd('steel drill')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9WcLEYmonMwK",
        "outputId": "89dea82a-19e7-4943-8a83-e3ad9c7871bd"
      },
      "execution_count": 46,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            " steel\n",
            " power\n",
            " use\n",
            " air\n",
            " volt\n",
            " tool\n",
            " cutting\n",
            " blade\n",
            " pipe\n",
            " designed\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#keyword- water\n",
        "disp_recomd('water')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "tDB2PAe6nUpn",
        "outputId": "556b0f75-da9f-4c02-ce2c-7c7d1f39b3ca"
      },
      "execution_count": 48,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            " shower\n",
            " water\n",
            " faucet\n",
            " sink\n",
            " valve\n",
            " drain\n",
            " handle\n",
            " tub\n",
            " brass\n",
            " design\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "-------------Ending----------"
      ],
      "metadata": {
        "id": "BRmy0UY8nijg"
      }
    }
  ]
}