Kaggle_Regression_HousingPrice.ipynb

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      "mount_file_id": "1tNrNjQwSE5CmizqThqEuMIs1RNks3bst",
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    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
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    "language_info": {
      "name": "python"
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  "cells": [
    {
      "cell_type": "markdown",
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        "colab_type": "text"
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      "source": [
        "<a href=\"https://colab.research.google.com/github/akshaypat444/cpython/blob/main/Kaggle_Regression_HousingPrice.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "wJPse7tufH7J"
      },
      "outputs": [],
      "source": [
        "import tensorflow as tf\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "from sklearn.model_selection import train_test_split"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "train_data = pd.read_csv(\"/content/drive/MyDrive/house-prices-advanced-regression-techniques/train.csv\")\n",
        "test_data = pd.read_csv(\"/content/drive/MyDrive/house-prices-advanced-regression-techniques/test.csv\")"
      ],
      "metadata": {
        "id": "Qi_MgBUefMZg"
      },
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "train_data.shape, test_data.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "trng5pSOm3Be",
        "outputId": "987fdc27-1b2b-4f12-9240-f340e0e8d915"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "((1460, 81), (1459, 80))"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "X_train = train_data.drop(\"SalePrice\", axis=1)\n",
        "y_train = train_data['SalePrice']\n",
        "\n",
        "X_test = train_data.drop(\"SalePrice\", axis=1)\n",
        "y_test = train_data['SalePrice']"
      ],
      "metadata": {
        "id": "BqgasKTdnEwb"
      },
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "pd.set_option('display.max_columns', None)\n",
        "pd.set_option('display.max_rows', None)\n",
        "\n",
        "train_data.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 226
        },
        "id": "xW1JacCCrFr2",
        "outputId": "a4bb0be6-065f-488f-cbad-88b85793c93d"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   Id  MSSubClass MSZoning  LotFrontage  LotArea Street Alley LotShape  \\\n",
              "0   1          60       RL         65.0     8450   Pave   NaN      Reg   \n",
              "1   2          20       RL         80.0     9600   Pave   NaN      Reg   \n",
              "2   3          60       RL         68.0    11250   Pave   NaN      IR1   \n",
              "3   4          70       RL         60.0     9550   Pave   NaN      IR1   \n",
              "4   5          60       RL         84.0    14260   Pave   NaN      IR1   \n",
              "\n",
              "  LandContour Utilities LotConfig LandSlope Neighborhood Condition1  \\\n",
              "0         Lvl    AllPub    Inside       Gtl      CollgCr       Norm   \n",
              "1         Lvl    AllPub       FR2       Gtl      Veenker      Feedr   \n",
              "2         Lvl    AllPub    Inside       Gtl      CollgCr       Norm   \n",
              "3         Lvl    AllPub    Corner       Gtl      Crawfor       Norm   \n",
              "4         Lvl    AllPub       FR2       Gtl      NoRidge       Norm   \n",
              "\n",
              "  Condition2 BldgType HouseStyle  OverallQual  OverallCond  YearBuilt  \\\n",
              "0       Norm     1Fam     2Story            7            5       2003   \n",
              "1       Norm     1Fam     1Story            6            8       1976   \n",
              "2       Norm     1Fam     2Story            7            5       2001   \n",
              "3       Norm     1Fam     2Story            7            5       1915   \n",
              "4       Norm     1Fam     2Story            8            5       2000   \n",
              "\n",
              "   YearRemodAdd RoofStyle RoofMatl Exterior1st Exterior2nd MasVnrType  \\\n",
              "0          2003     Gable  CompShg     VinylSd     VinylSd    BrkFace   \n",
              "1          1976     Gable  CompShg     MetalSd     MetalSd       None   \n",
              "2          2002     Gable  CompShg     VinylSd     VinylSd    BrkFace   \n",
              "3          1970     Gable  CompShg     Wd Sdng     Wd Shng       None   \n",
              "4          2000     Gable  CompShg     VinylSd     VinylSd    BrkFace   \n",
              "\n",
              "   MasVnrArea ExterQual ExterCond Foundation BsmtQual BsmtCond BsmtExposure  \\\n",
              "0       196.0        Gd        TA      PConc       Gd       TA           No   \n",
              "1         0.0        TA        TA     CBlock       Gd       TA           Gd   \n",
              "2       162.0        Gd        TA      PConc       Gd       TA           Mn   \n",
              "3         0.0        TA        TA     BrkTil       TA       Gd           No   \n",
              "4       350.0        Gd        TA      PConc       Gd       TA           Av   \n",
              "\n",
              "  BsmtFinType1  BsmtFinSF1 BsmtFinType2  BsmtFinSF2  BsmtUnfSF  TotalBsmtSF  \\\n",
              "0          GLQ         706          Unf           0        150          856   \n",
              "1          ALQ         978          Unf           0        284         1262   \n",
              "2          GLQ         486          Unf           0        434          920   \n",
              "3          ALQ         216          Unf           0        540          756   \n",
              "4          GLQ         655          Unf           0        490         1145   \n",
              "\n",
              "  Heating HeatingQC CentralAir Electrical  1stFlrSF  2ndFlrSF  LowQualFinSF  \\\n",
              "0    GasA        Ex          Y      SBrkr       856       854             0   \n",
              "1    GasA        Ex          Y      SBrkr      1262         0             0   \n",
              "2    GasA        Ex          Y      SBrkr       920       866             0   \n",
              "3    GasA        Gd          Y      SBrkr       961       756             0   \n",
              "4    GasA        Ex          Y      SBrkr      1145      1053             0   \n",
              "\n",
              "   GrLivArea  BsmtFullBath  BsmtHalfBath  FullBath  HalfBath  BedroomAbvGr  \\\n",
              "0       1710             1             0         2         1             3   \n",
              "1       1262             0             1         2         0             3   \n",
              "2       1786             1             0         2         1             3   \n",
              "3       1717             1             0         1         0             3   \n",
              "4       2198             1             0         2         1             4   \n",
              "\n",
              "   KitchenAbvGr KitchenQual  TotRmsAbvGrd Functional  Fireplaces FireplaceQu  \\\n",
              "0             1          Gd             8        Typ           0         NaN   \n",
              "1             1          TA             6        Typ           1          TA   \n",
              "2             1          Gd             6        Typ           1          TA   \n",
              "3             1          Gd             7        Typ           1          Gd   \n",
              "4             1          Gd             9        Typ           1          TA   \n",
              "\n",
              "  GarageType  GarageYrBlt GarageFinish  GarageCars  GarageArea GarageQual  \\\n",
              "0     Attchd       2003.0          RFn           2         548         TA   \n",
              "1     Attchd       1976.0          RFn           2         460         TA   \n",
              "2     Attchd       2001.0          RFn           2         608         TA   \n",
              "3     Detchd       1998.0          Unf           3         642         TA   \n",
              "4     Attchd       2000.0          RFn           3         836         TA   \n",
              "\n",
              "  GarageCond PavedDrive  WoodDeckSF  OpenPorchSF  EnclosedPorch  3SsnPorch  \\\n",
              "0         TA          Y           0           61              0          0   \n",
              "1         TA          Y         298            0              0          0   \n",
              "2         TA          Y           0           42              0          0   \n",
              "3         TA          Y           0           35            272          0   \n",
              "4         TA          Y         192           84              0          0   \n",
              "\n",
              "   ScreenPorch  PoolArea PoolQC Fence MiscFeature  MiscVal  MoSold  YrSold  \\\n",
              "0            0         0    NaN   NaN         NaN        0       2    2008   \n",
              "1            0         0    NaN   NaN         NaN        0       5    2007   \n",
              "2            0         0    NaN   NaN         NaN        0       9    2008   \n",
              "3            0         0    NaN   NaN         NaN        0       2    2006   \n",
              "4            0         0    NaN   NaN         NaN        0      12    2008   \n",
              "\n",
              "  SaleType SaleCondition  SalePrice  \n",
              "0       WD        Normal     208500  \n",
              "1       WD        Normal     181500  \n",
              "2       WD        Normal     223500  \n",
              "3       WD       Abnorml     140000  \n",
              "4       WD        Normal     250000  "
            ],
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Id</th>\n",
              "      <th>MSSubClass</th>\n",
              "      <th>MSZoning</th>\n",
              "      <th>LotFrontage</th>\n",
              "      <th>LotArea</th>\n",
              "      <th>Street</th>\n",
              "      <th>Alley</th>\n",
              "      <th>LotShape</th>\n",
              "      <th>LandContour</th>\n",
              "      <th>Utilities</th>\n",
              "      <th>LotConfig</th>\n",
              "      <th>LandSlope</th>\n",
              "      <th>Neighborhood</th>\n",
              "      <th>Condition1</th>\n",
              "      <th>Condition2</th>\n",
              "      <th>BldgType</th>\n",
              "      <th>HouseStyle</th>\n",
              "      <th>OverallQual</th>\n",
              "      <th>OverallCond</th>\n",
              "      <th>YearBuilt</th>\n",
              "      <th>YearRemodAdd</th>\n",
              "      <th>RoofStyle</th>\n",
              "      <th>RoofMatl</th>\n",
              "      <th>Exterior1st</th>\n",
              "      <th>Exterior2nd</th>\n",
              "      <th>MasVnrType</th>\n",
              "      <th>MasVnrArea</th>\n",
              "      <th>ExterQual</th>\n",
              "      <th>ExterCond</th>\n",
              "      <th>Foundation</th>\n",
              "      <th>BsmtQual</th>\n",
              "      <th>BsmtCond</th>\n",
              "      <th>BsmtExposure</th>\n",
              "      <th>BsmtFinType1</th>\n",
              "      <th>BsmtFinSF1</th>\n",
              "      <th>BsmtFinType2</th>\n",
              "      <th>BsmtFinSF2</th>\n",
              "      <th>BsmtUnfSF</th>\n",
              "      <th>TotalBsmtSF</th>\n",
              "      <th>Heating</th>\n",
              "      <th>HeatingQC</th>\n",
              "      <th>CentralAir</th>\n",
              "      <th>Electrical</th>\n",
              "      <th>1stFlrSF</th>\n",
              "      <th>2ndFlrSF</th>\n",
              "      <th>LowQualFinSF</th>\n",
              "      <th>GrLivArea</th>\n",
              "      <th>BsmtFullBath</th>\n",
              "      <th>BsmtHalfBath</th>\n",
              "      <th>FullBath</th>\n",
              "      <th>HalfBath</th>\n",
              "      <th>BedroomAbvGr</th>\n",
              "      <th>KitchenAbvGr</th>\n",
              "      <th>KitchenQual</th>\n",
              "      <th>TotRmsAbvGrd</th>\n",
              "      <th>Functional</th>\n",
              "      <th>Fireplaces</th>\n",
              "      <th>FireplaceQu</th>\n",
              "      <th>GarageType</th>\n",
              "      <th>GarageYrBlt</th>\n",
              "      <th>GarageFinish</th>\n",
              "      <th>GarageCars</th>\n",
              "      <th>GarageArea</th>\n",
              "      <th>GarageQual</th>\n",
              "      <th>GarageCond</th>\n",
              "      <th>PavedDrive</th>\n",
              "      <th>WoodDeckSF</th>\n",
              "      <th>OpenPorchSF</th>\n",
              "      <th>EnclosedPorch</th>\n",
              "      <th>3SsnPorch</th>\n",
              "      <th>ScreenPorch</th>\n",
              "      <th>PoolArea</th>\n",
              "      <th>PoolQC</th>\n",
              "      <th>Fence</th>\n",
              "      <th>MiscFeature</th>\n",
              "      <th>MiscVal</th>\n",
              "      <th>MoSold</th>\n",
              "      <th>YrSold</th>\n",
              "      <th>SaleType</th>\n",
              "      <th>SaleCondition</th>\n",
              "      <th>SalePrice</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>60</td>\n",
              "      <td>RL</td>\n",
              "      <td>65.0</td>\n",
              "      <td>8450</td>\n",
              "      <td>Pave</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Reg</td>\n",
              "      <td>Lvl</td>\n",
              "      <td>AllPub</td>\n",
              "      <td>Inside</td>\n",
              "      <td>Gtl</td>\n",
              "      <td>CollgCr</td>\n",
              "      <td>Norm</td>\n",
              "      <td>Norm</td>\n",
              "      <td>1Fam</td>\n",
              "      <td>2Story</td>\n",
              "      <td>7</td>\n",
              "      <td>5</td>\n",
              "      <td>2003</td>\n",
              "      <td>2003</td>\n",
              "      <td>Gable</td>\n",
              "      <td>CompShg</td>\n",
              "      <td>VinylSd</td>\n",
              "      <td>VinylSd</td>\n",
              "      <td>BrkFace</td>\n",
              "      <td>196.0</td>\n",
              "      <td>Gd</td>\n",
              "      <td>TA</td>\n",
              "      <td>PConc</td>\n",
              "      <td>Gd</td>\n",
              "      <td>TA</td>\n",
              "      <td>No</td>\n",
              "      <td>GLQ</td>\n",
              "      <td>706</td>\n",
              "      <td>Unf</td>\n",
              "      <td>0</td>\n",
              "      <td>150</td>\n",
              "      <td>856</td>\n",
              "      <td>GasA</td>\n",
              "      <td>Ex</td>\n",
              "      <td>Y</td>\n",
              "      <td>SBrkr</td>\n",
              "      <td>856</td>\n",
              "      <td>854</td>\n",
              "      <td>0</td>\n",
              "      <td>1710</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>Gd</td>\n",
              "      <td>8</td>\n",
              "      <td>Typ</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Attchd</td>\n",
              "      <td>2003.0</td>\n",
              "      <td>RFn</td>\n",
              "      <td>2</td>\n",
              "      <td>548</td>\n",
              "      <td>TA</td>\n",
              "      <td>TA</td>\n",
              "      <td>Y</td>\n",
              "      <td>0</td>\n",
              "      <td>61</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2008</td>\n",
              "      <td>WD</td>\n",
              "      <td>Normal</td>\n",
              "      <td>208500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>20</td>\n",
              "      <td>RL</td>\n",
              "      <td>80.0</td>\n",
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              "      <td>Reg</td>\n",
              "      <td>Lvl</td>\n",
              "      <td>AllPub</td>\n",
              "      <td>FR2</td>\n",
              "      <td>Gtl</td>\n",
              "      <td>Veenker</td>\n",
              "      <td>Feedr</td>\n",
              "      <td>Norm</td>\n",
              "      <td>1Fam</td>\n",
              "      <td>1Story</td>\n",
              "      <td>6</td>\n",
              "      <td>8</td>\n",
              "      <td>1976</td>\n",
              "      <td>1976</td>\n",
              "      <td>Gable</td>\n",
              "      <td>CompShg</td>\n",
              "      <td>MetalSd</td>\n",
              "      <td>MetalSd</td>\n",
              "      <td>None</td>\n",
              "      <td>0.0</td>\n",
              "      <td>TA</td>\n",
              "      <td>TA</td>\n",
              "      <td>CBlock</td>\n",
              "      <td>Gd</td>\n",
              "      <td>TA</td>\n",
              "      <td>Gd</td>\n",
              "      <td>ALQ</td>\n",
              "      <td>978</td>\n",
              "      <td>Unf</td>\n",
              "      <td>0</td>\n",
              "      <td>284</td>\n",
              "      <td>1262</td>\n",
              "      <td>GasA</td>\n",
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              "      <td>Y</td>\n",
              "      <td>SBrkr</td>\n",
              "      <td>1262</td>\n",
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              "      <td>6</td>\n",
              "      <td>Typ</td>\n",
              "      <td>1</td>\n",
              "      <td>TA</td>\n",
              "      <td>Attchd</td>\n",
              "      <td>1976.0</td>\n",
              "      <td>RFn</td>\n",
              "      <td>2</td>\n",
              "      <td>460</td>\n",
              "      <td>TA</td>\n",
              "      <td>TA</td>\n",
              "      <td>Y</td>\n",
              "      <td>298</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>5</td>\n",
              "      <td>2007</td>\n",
              "      <td>WD</td>\n",
              "      <td>Normal</td>\n",
              "      <td>181500</td>\n",
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              "      <th>2</th>\n",
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              "      <td>60</td>\n",
              "      <td>RL</td>\n",
              "      <td>68.0</td>\n",
              "      <td>11250</td>\n",
              "      <td>Pave</td>\n",
              "      <td>NaN</td>\n",
              "      <td>IR1</td>\n",
              "      <td>Lvl</td>\n",
              "      <td>AllPub</td>\n",
              "      <td>Inside</td>\n",
              "      <td>Gtl</td>\n",
              "      <td>CollgCr</td>\n",
              "      <td>Norm</td>\n",
              "      <td>Norm</td>\n",
              "      <td>1Fam</td>\n",
              "      <td>2Story</td>\n",
              "      <td>7</td>\n",
              "      <td>5</td>\n",
              "      <td>2001</td>\n",
              "      <td>2002</td>\n",
              "      <td>Gable</td>\n",
              "      <td>CompShg</td>\n",
              "      <td>VinylSd</td>\n",
              "      <td>VinylSd</td>\n",
              "      <td>BrkFace</td>\n",
              "      <td>162.0</td>\n",
              "      <td>Gd</td>\n",
              "      <td>TA</td>\n",
              "      <td>PConc</td>\n",
              "      <td>Gd</td>\n",
              "      <td>TA</td>\n",
              "      <td>Mn</td>\n",
              "      <td>GLQ</td>\n",
              "      <td>486</td>\n",
              "      <td>Unf</td>\n",
              "      <td>0</td>\n",
              "      <td>434</td>\n",
              "      <td>920</td>\n",
              "      <td>GasA</td>\n",
              "      <td>Ex</td>\n",
              "      <td>Y</td>\n",
              "      <td>SBrkr</td>\n",
              "      <td>920</td>\n",
              "      <td>866</td>\n",
              "      <td>0</td>\n",
              "      <td>1786</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>Gd</td>\n",
              "      <td>6</td>\n",
              "      <td>Typ</td>\n",
              "      <td>1</td>\n",
              "      <td>TA</td>\n",
              "      <td>Attchd</td>\n",
              "      <td>2001.0</td>\n",
              "      <td>RFn</td>\n",
              "      <td>2</td>\n",
              "      <td>608</td>\n",
              "      <td>TA</td>\n",
              "      <td>TA</td>\n",
              "      <td>Y</td>\n",
              "      <td>0</td>\n",
              "      <td>42</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>9</td>\n",
              "      <td>2008</td>\n",
              "      <td>WD</td>\n",
              "      <td>Normal</td>\n",
              "      <td>223500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>70</td>\n",
              "      <td>RL</td>\n",
              "      <td>60.0</td>\n",
              "      <td>9550</td>\n",
              "      <td>Pave</td>\n",
              "      <td>NaN</td>\n",
              "      <td>IR1</td>\n",
              "      <td>Lvl</td>\n",
              "      <td>AllPub</td>\n",
              "      <td>Corner</td>\n",
              "      <td>Gtl</td>\n",
              "      <td>Crawfor</td>\n",
              "      <td>Norm</td>\n",
              "      <td>Norm</td>\n",
              "      <td>1Fam</td>\n",
              "      <td>2Story</td>\n",
              "      <td>7</td>\n",
              "      <td>5</td>\n",
              "      <td>1915</td>\n",
              "      <td>1970</td>\n",
              "      <td>Gable</td>\n",
              "      <td>CompShg</td>\n",
              "      <td>Wd Sdng</td>\n",
              "      <td>Wd Shng</td>\n",
              "      <td>None</td>\n",
              "      <td>0.0</td>\n",
              "      <td>TA</td>\n",
              "      <td>TA</td>\n",
              "      <td>BrkTil</td>\n",
              "      <td>TA</td>\n",
              "      <td>Gd</td>\n",
              "      <td>No</td>\n",
              "      <td>ALQ</td>\n",
              "      <td>216</td>\n",
              "      <td>Unf</td>\n",
              "      <td>0</td>\n",
              "      <td>540</td>\n",
              "      <td>756</td>\n",
              "      <td>GasA</td>\n",
              "      <td>Gd</td>\n",
              "      <td>Y</td>\n",
              "      <td>SBrkr</td>\n",
              "      <td>961</td>\n",
              "      <td>756</td>\n",
              "      <td>0</td>\n",
              "      <td>1717</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>Gd</td>\n",
              "      <td>7</td>\n",
              "      <td>Typ</td>\n",
              "      <td>1</td>\n",
              "      <td>Gd</td>\n",
              "      <td>Detchd</td>\n",
              "      <td>1998.0</td>\n",
              "      <td>Unf</td>\n",
              "      <td>3</td>\n",
              "      <td>642</td>\n",
              "      <td>TA</td>\n",
              "      <td>TA</td>\n",
              "      <td>Y</td>\n",
              "      <td>0</td>\n",
              "      <td>35</td>\n",
              "      <td>272</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2006</td>\n",
              "      <td>WD</td>\n",
              "      <td>Abnorml</td>\n",
              "      <td>140000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>60</td>\n",
              "      <td>RL</td>\n",
              "      <td>84.0</td>\n",
              "      <td>14260</td>\n",
              "      <td>Pave</td>\n",
              "      <td>NaN</td>\n",
              "      <td>IR1</td>\n",
              "      <td>Lvl</td>\n",
              "      <td>AllPub</td>\n",
              "      <td>FR2</td>\n",
              "      <td>Gtl</td>\n",
              "      <td>NoRidge</td>\n",
              "      <td>Norm</td>\n",
              "      <td>Norm</td>\n",
              "      <td>1Fam</td>\n",
              "      <td>2Story</td>\n",
              "      <td>8</td>\n",
              "      <td>5</td>\n",
              "      <td>2000</td>\n",
              "      <td>2000</td>\n",
              "      <td>Gable</td>\n",
              "      <td>CompShg</td>\n",
              "      <td>VinylSd</td>\n",
              "      <td>VinylSd</td>\n",
              "      <td>BrkFace</td>\n",
              "      <td>350.0</td>\n",
              "      <td>Gd</td>\n",
              "      <td>TA</td>\n",
              "      <td>PConc</td>\n",
              "      <td>Gd</td>\n",
              "      <td>TA</td>\n",
              "      <td>Av</td>\n",
              "      <td>GLQ</td>\n",
              "      <td>655</td>\n",
              "      <td>Unf</td>\n",
              "      <td>0</td>\n",
              "      <td>490</td>\n",
              "      <td>1145</td>\n",
              "      <td>GasA</td>\n",
              "      <td>Ex</td>\n",
              "      <td>Y</td>\n",
              "      <td>SBrkr</td>\n",
              "      <td>1145</td>\n",
              "      <td>1053</td>\n",
              "      <td>0</td>\n",
              "      <td>2198</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>Gd</td>\n",
              "      <td>9</td>\n",
              "      <td>Typ</td>\n",
              "      <td>1</td>\n",
              "      <td>TA</td>\n",
              "      <td>Attchd</td>\n",
              "      <td>2000.0</td>\n",
              "      <td>RFn</td>\n",
              "      <td>3</td>\n",
              "      <td>836</td>\n",
              "      <td>TA</td>\n",
              "      <td>TA</td>\n",
              "      <td>Y</td>\n",
              "      <td>192</td>\n",
              "      <td>84</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>12</td>\n",
              "      <td>2008</td>\n",
              "      <td>WD</td>\n",
              "      <td>Normal</td>\n",
              "      <td>250000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
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              "            title=\"Convert this dataframe to an interactive table.\"\n",
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              "    </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-a39d11a5-5a5d-4f5e-9663-5ece64964718 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-a39d11a5-5a5d-4f5e-9663-5ece64964718');\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-5906f9ee-cd42-458e-bf22-959c8891c283\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-5906f9ee-cd42-458e-bf22-959c8891c283')\"\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",
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              "    </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",
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              "      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-5906f9ee-cd42-458e-bf22-959c8891c283 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.compose import make_column_transformer\n",
        "from sklearn.preprocessing import MinMaxScaler, OneHotEncoder\n",
        "\n",
        "ct = make_column_transformer(\n",
        "    (MinMaxScaler(), [\"LotArea\", \"YrSold\", \"MoSold\", \"OverallQual\", \"OverallCond\", \"YearBuilt\",  \"1stFlrSF\", \"2ndFlrSF\", \"GrLivArea\",\n",
        "                      \"BsmtFullBath\",\"BsmtHalfBath\",\t\"FullBath\" ,\t\"HalfBath\" ,\t\"BedroomAbvGr\" ,\t\"KitchenAbvGr\", \"TotRmsAbvGrd\", \"Fireplaces\",\n",
        "                      \"GarageCars\", \"YrSold\"]),\n",
        "    (OneHotEncoder(handle_unknown=\"ignore\"), [\"Street\", \"SaleCondition\", \"LotShape\", \"Utilities\", \"LotConfig\", \"HouseStyle\"])\n",
        ")\n",
        "\n",
        "X_train = train_data.drop(\"SalePrice\", axis=1)\n",
        "y_train = train_data[\"SalePrice\"]\n",
        "\n",
        "X_test = test_data\n",
        "\n",
        "ct.fit(X_train)\n",
        "\n",
        "X_train_normal = ct.transform(X_train)\n",
        "X_test_normal = ct.transform(X_test)"
      ],
      "metadata": {
        "id": "dPTRCi7fnOUk"
      },
      "execution_count": 32,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Model 1"
      ],
      "metadata": {
        "id": "mLG0VkvBuEIc"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "tf.random.set_seed(42)\n",
        "\n",
        "# Create a Model\n",
        "housing_price_model = tf.keras.Sequential([\n",
        "     tf.keras.layers.Dense(100),\n",
        "     tf.keras.layers.Dense(50),\n",
        "     tf.keras.layers.Dense(30),\n",
        "     tf.keras.layers.Dense(20),\n",
        "     tf.keras.layers.Dense(5),\n",
        "     tf.keras.layers.Dense(1)\n",
        "])\n",
        "\n",
        "# Compile the model\n",
        "housing_price_model.compile(loss=tf.keras.losses.mae,\n",
        "                                   optimizer=tf.keras.optimizers.Adam(learning_rate=0.01),\n",
        "                                   metrics=[\"mae\"])\n",
        "\n",
        "# Fit the model\n",
        "history = housing_price_model.fit(X_train_normal, y_train, epochs=100)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LF-DY3bouDo7",
        "outputId": "c1541c14-a1b0-4684-faf2-b4f72910e683"
      },
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/100\n",
            "46/46 [==============================] - 1s 2ms/step - loss: 112604.8203 - mae: 112604.8203\n",
            "Epoch 2/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 38659.8320 - mae: 38659.8320\n",
            "Epoch 3/100\n",
            "46/46 [==============================] - 0s 1ms/step - loss: 32175.7969 - mae: 32175.7969\n",
            "Epoch 4/100\n",
            "46/46 [==============================] - 0s 1ms/step - loss: 29080.3457 - mae: 29080.3457\n",
            "Epoch 5/100\n",
            "46/46 [==============================] - 0s 1ms/step - loss: 27522.9805 - mae: 27522.9805\n",
            "Epoch 6/100\n",
            "46/46 [==============================] - 0s 1ms/step - loss: 27577.3789 - mae: 27577.3789\n",
            "Epoch 7/100\n",
            "46/46 [==============================] - 0s 1ms/step - loss: 24666.2715 - mae: 24666.2715\n",
            "Epoch 8/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 23138.8652 - mae: 23138.8652\n",
            "Epoch 9/100\n",
            "46/46 [==============================] - 0s 1ms/step - loss: 22658.2402 - mae: 22658.2402\n",
            "Epoch 10/100\n",
            "46/46 [==============================] - 0s 1ms/step - loss: 23436.1348 - mae: 23436.1348\n",
            "Epoch 11/100\n",
            "46/46 [==============================] - 0s 1ms/step - loss: 22323.0332 - mae: 22323.0332\n",
            "Epoch 12/100\n",
            "46/46 [==============================] - 0s 1ms/step - loss: 22304.3145 - mae: 22304.3145\n",
            "Epoch 13/100\n",
            "46/46 [==============================] - 0s 1ms/step - loss: 22446.1582 - mae: 22446.1582\n",
            "Epoch 14/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 21935.3867 - mae: 21935.3867\n",
            "Epoch 15/100\n",
            "46/46 [==============================] - 0s 1ms/step - loss: 21997.1738 - mae: 21997.1738\n",
            "Epoch 16/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 21766.9316 - mae: 21766.9316\n",
            "Epoch 17/100\n",
            "46/46 [==============================] - 0s 1ms/step - loss: 22937.4609 - mae: 22937.4609\n",
            "Epoch 18/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 22180.9355 - mae: 22180.9355\n",
            "Epoch 19/100\n",
            "46/46 [==============================] - 0s 1ms/step - loss: 21249.0977 - mae: 21249.0977\n",
            "Epoch 20/100\n",
            "46/46 [==============================] - 0s 1ms/step - loss: 21439.0391 - mae: 21439.0391\n",
            "Epoch 21/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 23223.5977 - mae: 23223.5977\n",
            "Epoch 22/100\n",
            "46/46 [==============================] - 0s 1ms/step - loss: 21182.4004 - mae: 21182.4004\n",
            "Epoch 23/100\n",
            "46/46 [==============================] - 0s 1ms/step - loss: 21667.4434 - mae: 21667.4434\n",
            "Epoch 24/100\n",
            "46/46 [==============================] - 0s 1ms/step - loss: 21929.6992 - mae: 21929.6992\n",
            "Epoch 25/100\n",
            "46/46 [==============================] - 0s 1ms/step - loss: 21445.7051 - mae: 21445.7051\n",
            "Epoch 26/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 21054.3633 - mae: 21054.3633\n",
            "Epoch 27/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 21115.2969 - mae: 21115.2969\n",
            "Epoch 28/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 21827.5410 - mae: 21827.5410\n",
            "Epoch 29/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 21078.0293 - mae: 21078.0293\n",
            "Epoch 30/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 22185.7656 - mae: 22185.7656\n",
            "Epoch 31/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 21543.9648 - mae: 21543.9648\n",
            "Epoch 32/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 21265.5215 - mae: 21265.5215\n",
            "Epoch 33/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 21122.9609 - mae: 21122.9609\n",
            "Epoch 34/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 21096.0352 - mae: 21096.0352\n",
            "Epoch 35/100\n",
            "46/46 [==============================] - 0s 1ms/step - loss: 21137.2852 - mae: 21137.2852\n",
            "Epoch 36/100\n",
            "46/46 [==============================] - 0s 1ms/step - loss: 22151.2910 - mae: 22151.2910\n",
            "Epoch 37/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 22207.3730 - mae: 22207.3730\n",
            "Epoch 38/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 21355.8008 - mae: 21355.8008\n",
            "Epoch 39/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 21394.9551 - mae: 21394.9551\n",
            "Epoch 40/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 21241.1680 - mae: 21241.1680\n",
            "Epoch 41/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 21705.2305 - mae: 21705.2305\n",
            "Epoch 42/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 21632.3262 - mae: 21632.3262\n",
            "Epoch 43/100\n",
            "46/46 [==============================] - 0s 1ms/step - loss: 22038.3105 - mae: 22038.3105\n",
            "Epoch 44/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 21920.3457 - mae: 21920.3457\n",
            "Epoch 45/100\n",
            "46/46 [==============================] - 0s 1ms/step - loss: 21545.7129 - mae: 21545.7129\n",
            "Epoch 46/100\n",
            "46/46 [==============================] - 0s 1ms/step - loss: 23306.1016 - mae: 23306.1016\n",
            "Epoch 47/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 21852.1582 - mae: 21852.1582\n",
            "Epoch 48/100\n",
            "46/46 [==============================] - 0s 1ms/step - loss: 21237.6484 - mae: 21237.6484\n",
            "Epoch 49/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 21632.9922 - mae: 21632.9922\n",
            "Epoch 50/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 21965.3398 - mae: 21965.3398\n",
            "Epoch 51/100\n",
            "46/46 [==============================] - 0s 1ms/step - loss: 21814.7012 - mae: 21814.7012\n",
            "Epoch 52/100\n",
            "46/46 [==============================] - 0s 1ms/step - loss: 21181.5762 - mae: 21181.5762\n",
            "Epoch 53/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 21302.8086 - mae: 21302.8086\n",
            "Epoch 54/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 22028.9121 - mae: 22028.9121\n",
            "Epoch 55/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 22423.5098 - mae: 22423.5098\n",
            "Epoch 56/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 21396.6309 - mae: 21396.6309\n",
            "Epoch 57/100\n",
            "46/46 [==============================] - 0s 1ms/step - loss: 21385.1074 - mae: 21385.1074\n",
            "Epoch 58/100\n",
            "46/46 [==============================] - 0s 1ms/step - loss: 22004.6348 - mae: 22004.6348\n",
            "Epoch 59/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 23456.0020 - mae: 23456.0020\n",
            "Epoch 60/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 22331.6094 - mae: 22331.6094\n",
            "Epoch 61/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 23598.3340 - mae: 23598.3340\n",
            "Epoch 62/100\n",
            "46/46 [==============================] - 0s 1ms/step - loss: 22154.7637 - mae: 22154.7637\n",
            "Epoch 63/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 21425.2871 - mae: 21425.2871\n",
            "Epoch 64/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 21487.0566 - mae: 21487.0566\n",
            "Epoch 65/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 20908.1289 - mae: 20908.1289\n",
            "Epoch 66/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 21956.3867 - mae: 21956.3867\n",
            "Epoch 67/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 21226.5273 - mae: 21226.5273\n",
            "Epoch 68/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 21075.2871 - mae: 21075.2871\n",
            "Epoch 69/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 22090.4551 - mae: 22090.4551\n",
            "Epoch 70/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 22101.4336 - mae: 22101.4336\n",
            "Epoch 71/100\n",
            "46/46 [==============================] - 0s 1ms/step - loss: 21502.9922 - mae: 21502.9922\n",
            "Epoch 72/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 21813.0645 - mae: 21813.0645\n",
            "Epoch 73/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 22658.3105 - mae: 22658.3105\n",
            "Epoch 74/100\n",
            "46/46 [==============================] - 0s 1ms/step - loss: 20918.8926 - mae: 20918.8926\n",
            "Epoch 75/100\n",
            "46/46 [==============================] - 0s 1ms/step - loss: 21773.7676 - mae: 21773.7676\n",
            "Epoch 76/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 21596.1895 - mae: 21596.1895\n",
            "Epoch 77/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 21291.8594 - mae: 21291.8594\n",
            "Epoch 78/100\n",
            "46/46 [==============================] - 0s 1ms/step - loss: 23729.0840 - mae: 23729.0840\n",
            "Epoch 79/100\n",
            "46/46 [==============================] - 0s 1ms/step - loss: 21382.5840 - mae: 21382.5840\n",
            "Epoch 80/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 21435.9316 - mae: 21435.9316\n",
            "Epoch 81/100\n",
            "46/46 [==============================] - 0s 1ms/step - loss: 21510.4648 - mae: 21510.4648\n",
            "Epoch 82/100\n",
            "46/46 [==============================] - 0s 1ms/step - loss: 21767.4785 - mae: 21767.4785\n",
            "Epoch 83/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 21560.9375 - mae: 21560.9375\n",
            "Epoch 84/100\n",
            "46/46 [==============================] - 0s 1ms/step - loss: 21420.5488 - mae: 21420.5488\n",
            "Epoch 85/100\n",
            "46/46 [==============================] - 0s 1ms/step - loss: 21825.0957 - mae: 21825.0957\n",
            "Epoch 86/100\n",
            "46/46 [==============================] - 0s 1ms/step - loss: 22068.4277 - mae: 22068.4277\n",
            "Epoch 87/100\n",
            "46/46 [==============================] - 0s 1ms/step - loss: 21202.8418 - mae: 21202.8418\n",
            "Epoch 88/100\n",
            "46/46 [==============================] - 0s 1ms/step - loss: 21230.6895 - mae: 21230.6895\n",
            "Epoch 89/100\n",
            "46/46 [==============================] - 0s 1ms/step - loss: 21054.4688 - mae: 21054.4688\n",
            "Epoch 90/100\n",
            "46/46 [==============================] - 0s 1ms/step - loss: 21279.6445 - mae: 21279.6445\n",
            "Epoch 91/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 20898.1055 - mae: 20898.1055\n",
            "Epoch 92/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 20770.3750 - mae: 20770.3750\n",
            "Epoch 93/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 22076.0020 - mae: 22076.0020\n",
            "Epoch 94/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 21182.1230 - mae: 21182.1230\n",
            "Epoch 95/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 21936.0312 - mae: 21936.0312\n",
            "Epoch 96/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 21371.5215 - mae: 21371.5215\n",
            "Epoch 97/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 21440.2949 - mae: 21440.2949\n",
            "Epoch 98/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 22479.8613 - mae: 22479.8613\n",
            "Epoch 99/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 21658.6973 - mae: 21658.6973\n",
            "Epoch 100/100\n",
            "46/46 [==============================] - 0s 2ms/step - loss: 21394.0762 - mae: 21394.0762\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# loss: 34174.3555 - mae: 34174.3555\n",
        "# loss: 20850.5898 - mae: 20850.5898\n",
        "# loss: 21394.0762 - mae: 21394.0762"
      ],
      "metadata": {
        "id": "x5bTJRzotSzB"
      },
      "execution_count": 63,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "pd.DataFrame(history.history).plot()\n",
        "plt.ylabel(\"loss\")\n",
        "plt.xlabel(\"epochs\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 467
        },
        "id": "JiEy-RrXt7AE",
        "outputId": "fb31a415-3be2-4b14-9bca-c1d5e014e963"
      },
      "execution_count": 42,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 0, 'epochs')"
            ]
          },
          "metadata": {},
          "execution_count": 42
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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3CfGSSaT+sNDtxyYiImrO6vr+LQkhhIKZrlmxWq0ICAiAxWJx+/qqPW/Go3dlKrb3fg0D7v6nW49NRETUnNX1/bvRrqmi+nFo9Oe+4PQfERGREhiqVELwPlVERESKYqhSiT9DFT/7j4iISAkMVSohNLVX/3H6j4iISBkMVSohJIYqIiIiJTFUqYTQ1E7/gWuqiIiIFMFQpRLO6T/eUZ2IiEgZDFVqcW76T2KoIiIiUgRDlUr8OVLFq/+IiIiUwFClFhrnSJVd4UKIiIiaJ4YqleAtFYiIiJTFUKUSkjxSxek/IiIiJTBUqYQ8UiU4/UdERKQEhiq10PLqPyIiIiUxVKmExIXqREREimKoUgtnqBIcqSIiIlICQ5VaaDj9R0REpCSGKpWQtPraP7lQnYiISBEMVSohnVuoruH0HxERkSIYqtSC039ERESKYqhSCc256T8Np/+IiIgUwVClEpz+IyIiUhZDlUr8Gao4UkVERKQEhiqV0GgNtX8yVBERESmCoUolOP1HRESkLIYqldA4QxU4UkVERKQEhiqVkHS1V/9pOf1HRESkCIYqlZBvqcCRKiIiIkUwVKmEc/pPyzVVREREimCoUgnnSJVWOBSuhIiIqHliqFIJrY7Tf0REREpiqFIJzblQpQOn/4iIiJTAUKUS8vQfR6qIiIgUwVClEjo911QREREpiaFKJZxX/3H6j4iISBkMVSqh1dV+9p8WHKkiIiJSAkOVSjiv/tNLdggHgxUREZGnMVSphO5cqAIAu51TgERERJ7GUKUSmvNClc1Wo2AlREREzRNDlUro9Qb5aztDFRERkccxVKmE1mWkitN/REREnsZQpRIua6pqqhSshIiIqHliqFIJSaOBTdT+OB0cqSIiIvI4hioVsUMLALDZuaaKiIjI0xiqVMR+7sdpr2GoIiIi8jSGKhWxSbUjVQ57tcKVEBERNT8MVSpiR+3n/3FNFRERkecxVKmIc/qPN/8kIiLyPIYqFXEuVHdwoToREZHHMVSpiF1yTv8xVBEREXkaQ5WKcKSKiIhIOQxVKuJwXv3HhepEREQex1ClIn+OVDFUEREReRpDlYo4eJ8qIiIixTBUqYgzVAmOVBEREXkcQ5WKyFf/MVQRERF5HEOVinCkioiISDkMVSoi5FDFNVVERESexlClIo5z038cqSIiIvI8hioVcYYqOBiqiIiIPI2hSkWExDuqExERKYWhSkWEpjZUcaSKiIjI8xiqVMQh6QFwTRUREZESGnWostvtmDlzJiIjI+Ht7Y2OHTvi1VdfhRBCbiOEwKxZsxAaGgpvb2/Ex8fj4MGDLscpLCxEYmIiTCYTAgMDMW7cOJSWlrq02bt3L66//np4eXkhPDwcs2fPvqCe5cuXo2vXrvDy8kJ0dDRWr159dV54A/05UsXpPyIiIk9r1KHqrbfewsKFCzF//nxkZWXhrbfewuzZs/H+++/LbWbPno158+Zh0aJFSElJga+vLxISElBZWSm3SUxMREZGBtauXYuVK1di8+bNmDBhgrzfarViyJAhaN++PdLS0jBnzhy8/PLL+Oijj+Q2W7duxZgxYzBu3Djs2rULw4cPx/Dhw7Fv3z7PdEYdCF79R0REpBzRiA0bNkw88sgjLttGjBghEhMThRBCOBwOERISIubMmSPvLy4uFkajUXz99ddCCCEyMzMFAJGamiq3WbNmjZAkSZw4cUIIIcQHH3wggoKCRFVVldzmmWeeEVFRUfL3o0aNEsOGDXOpJTY2Vjz22GOXrL+yslJYLBb5kZeXJwAIi8VS366ok23v3S/ESyax9dOnr8rxiYiImiOLxVKn9+9GPVI1cOBArFu3DgcOHAAA7NmzB3/88Qduu+02AMDRo0dhNpsRHx8vPycgIACxsbFITk4GACQnJyMwMBAxMTFym/j4eGg0GqSkpMhtbrjhBhgMBrlNQkICsrOzUVRUJLc5/zzONs7zXExSUhICAgLkR3h4+JV0x+VpeEsFIiIipeiULuCvPPvss7BarejatSu0Wi3sdjtef/11JCYmAgDMZjMAIDg42OV5wcHB8j6z2Yw2bdq47NfpdGjRooVLm8jIyAuO4dwXFBQEs9n8l+e5mOeeew7Tp0+Xv7darVc1WDlvqcBQRURE5HmNOlQtW7YMX375Jb766iv06NEDu3fvxtSpUxEWFoaxY8cqXd5lGY1GGI1Gz52QI1VERESKadShasaMGXj22WcxevRoAEB0dDRycnKQlJSEsWPHIiQkBACQn5+P0NBQ+Xn5+fno06cPACAkJAQFBQUux7XZbCgsLJSfHxISgvz8fJc2zu8v18a5vzEQmtpbKkgOu8KVEBERNT+Nek1VeXk5NBrXErVaLRwOBwAgMjISISEhWLdunbzfarUiJSUFcXFxAIC4uDgUFxcjLS1NbrN+/Xo4HA7ExsbKbTZv3oyamj9vRbB27VpERUUhKChIbnP+eZxtnOdpFM7dUkHiLRWIiIg8rlGHqjvvvBOvv/46Vq1ahWPHjmHFihV4++23cffddwMAJEnC1KlT8dprr+HHH39Eeno6HnzwQYSFhWH48OEAgG7dumHo0KEYP348tm/fji1btmDy5MkYPXo0wsLCAAD33XcfDAYDxo0bh4yMDCxduhTvvfeey3qoKVOm4Oeff8bcuXOxf/9+vPzyy9ixYwcmT57s8X65JE7/ERERKcdDVyM2iNVqFVOmTBERERHCy8tLXHPNNeKFF15wufWBw+EQM2fOFMHBwcJoNIpbbrlFZGdnuxzn7NmzYsyYMcLPz0+YTCbx8MMPi5KSEpc2e/bsEYMHDxZGo1G0bdtWvPnmmxfUs2zZMtGlSxdhMBhEjx49xKpVq+r1eup6SWZDbf3sGSFeMomU9xKvyvGJiIiao7q+f0tCnHd7crqqrFYrAgICYLFYYDKZ3H785C9mIu7IPKQG3oZrpy5x+/GJiIiao7q+fzfq6T+qH0leU8XpPyIiIk9jqFIT7bmr/wSv/iMiIvI0hioVkc4tVOdIFRERkecxVKmJM1QJhioiIiJPY6hSEUlXO/2n4fQfERGRxzFUqYjEkSoiIiLFMFSpiKStDVUcqSIiIvI8hioV0Wg5/UdERKQUhioVkRiqiIiIFMNQpSJ/Tv9xTRUREZGnMVSpiEbDNVVERERKYahSEc25WypoGaqIiIg8jqFKReQ1VeD0HxERkacxVKmI9tyaKo5UEREReR5DlYpo9IbaP8FQRURE5GkMVSqiOTdSpePVf0RERB7HUKUi8s0/4VC4EiIiouaHoUpFtM6r/zj9R0RE5HEMVSrivKUCp/+IiIg8j6FKRbRa50gVp/+IiIg8jaFKRbT6cyNVnP4jIiLyOIYqFXGuqWKoIiIi8jyGKhVxTv9pJAGHncGKiIjIkxiqVMS5UB0AbLYaBSshIiJqfhiqVESv/zNU2RmqiIiIPIqhSkW0541U1dRUK1gJERFR88NQpSI6nUH+2sGRKiIiIo9iqFIRrU4Hh5AAcE0VERGRpzFUqYzt3I/UbuP0HxERkScxVKmMHdraP238qBoiIiJPYqhSGdu5UMU1VURERJ7FUKUydsk5UsXpPyIiIk9qUKj6/PPPsWrVKvn7p59+GoGBgRg4cCBycnLcVhzVn3P6z2HnSBUREZEnNShUvfHGG/D29gYAJCcnY8GCBZg9ezZatWqFadOmubVAqh+uqSIiIlKGriFPysvLQ6dOnQAA33//PUaOHIkJEyZg0KBBuOmmm9xZH9UTR6qIiIiU0aCRKj8/P5w9exYA8Ouvv+LWW28FAHh5eaGiosJ91VG9OddUcaE6ERGRZzVopOrWW2/Fo48+ir59++LAgQO4/fbbAQAZGRno0KGDO+ujenJIWkAADjun/4iIiDypQSNVCxYsQFxcHE6fPo1vv/0WLVu2BACkpaVhzJgxbi2Q6sd+Lidz+o+IiMizGjRSFRgYiPnz51+w/ZVXXrnigujKODj9R0REpIgGjVT9/PPP+OOPP+TvFyxYgD59+uC+++5DUVGR24qj+nOGKuFgqCIiIvKkBoWqGTNmwGq1AgDS09Px5JNP4vbbb8fRo0cxffp0txZI9SNP//GWCkRERB7VoOm/o0ePonv37gCAb7/9FnfccQfeeOMN7Ny5U160TsqQR6q4poqIiMijGjRSZTAYUF5eDgD47bffMGTIEABAixYt5BEsUoZwrqlycKSKiIjIkxo0UjV48GBMnz4dgwYNwvbt27F06VIAwIEDB9CuXTu3Fkj1Y9ec+5HylgpEREQe1aCRqvnz50On0+Gbb77BwoUL0bZtWwDAmjVrMHToULcWSPUjj1Rx+o+IiMijGjRSFRERgZUrV16w/Z133rnigujKOCSOVBERESmhQaEKAOx2O77//ntkZWUBAHr06IG//e1v0Gq1biuO6k+cC1WCa6qIiIg8qkGh6tChQ7j99ttx4sQJREVFAQCSkpIQHh6OVatWoWPHjm4tkupOaHj1HxERkRIatKbqiSeeQMeOHZGXl4edO3di586dyM3NRWRkJJ544gl310j14FxTBY5UEREReVSDRqo2bdqEbdu2oUWLFvK2li1b4s0338SgQYPcVhzVn+CaKiIiIkU0aKTKaDSipKTkgu2lpaUwGAxXXBQ1nHDeUsFhV7YQIiKiZqZBoeqOO+7AhAkTkJKSAiEEhBDYtm0bHn/8cfztb39zd41UD85Qxc/+IyIi8qwGhap58+ahY8eOiIuLg5eXF7y8vDBw4EB06tQJ7777rptLpHrhmioiIiJFNGhNVWBgIH744QccOnRIvqVCt27d0KlTJ7cWR/UntPraLxiqiIiIPKrOoWr69Ol/uX/Dhg3y12+//XbDK6Irc26kSuItFYiIiDyqzqFq165ddWonSVKDi6ErJy9UF1yoTkRE5El1DlXnj0RRI3Zu+k/i9B8REZFHNWihOjVi8i0VGKqIiIg8iaFKbc59TA1HqoiIiDyLoUplJOf0H9dUEREReRRDldqcm/7jSBUREZFnMVSpjHQuVGkEQxUREZEnNfpQdeLECdx///1o2bIlvL29ER0djR07dsj7hRCYNWsWQkND4e3tjfj4eBw8eNDlGIWFhUhMTITJZEJgYCDGjRuH0tJSlzZ79+7F9ddfDy8vL4SHh2P27NkX1LJ8+XJ07doVXl5eiI6OxurVq6/Oi74SzpEqTv8RERF5VKMOVUVFRRg0aBD0ej3WrFmDzMxMzJ07F0FBQXKb2bNnY968eVi0aBFSUlLg6+uLhIQEVFZWym0SExORkZGBtWvXYuXKldi8eTMmTJgg77darRgyZAjat2+PtLQ0zJkzBy+//DI++ugjuc3WrVsxZswYjBs3Drt27cLw4cMxfPhw7Nu3zzOdUUcSb6lARESkDNGIPfPMM2Lw4MGX3O9wOERISIiYM2eOvK24uFgYjUbx9ddfCyGEyMzMFABEamqq3GbNmjVCkiRx4sQJIYQQH3zwgQgKChJVVVUu546KipK/HzVqlBg2bJjL+WNjY8Vjjz12yfoqKyuFxWKRH3l5eQKAsFgsdeyB+tu+4n0hXjKJPUm3XLVzEBERNScWi6VO79+NeqTqxx9/RExMDO655x60adMGffv2xccffyzvP3r0KMxmM+Lj4+VtAQEBiI2NRXJyMgAgOTkZgYGBiImJkdvEx8dDo9EgJSVFbnPDDTfAYDDIbRISEpCdnY2ioiK5zfnncbZxnudikpKSEBAQID/Cw8OvoDfqRpKn/zhSRURE5EmNOlQdOXIECxcuROfOnfHLL79g4sSJeOKJJ/D5558DAMxmMwAgODjY5XnBwcHyPrPZjDZt2rjs1+l0aNGihUubix3j/HNcqo1z/8U899xzsFgs8iMvL69er78hJF3t9J+Ga6qIiIg8qs4fU6MEh8OBmJgYvPHGGwCAvn37Yt++fVi0aBHGjh2rcHWXZzQaYTQaPXpOjZZX/xERESmhUY9UhYaGonv37i7bunXrhtzcXABASEgIACA/P9+lTX5+vrwvJCQEBQUFLvttNhsKCwtd2lzsGOef41JtnPsbC0nDkSoiIiIlNOpQNWjQIGRnZ7tsO3DgANq3bw8AiIyMREhICNatWyfvt1qtSElJQVxcHAAgLi4OxcXFSEtLk9usX78eDocDsbGxcpvNmzejpqZGbrN27VpERUXJVxrGxcW5nMfZxnmexoLTf0RERMpo1KFq2rRp2LZtG9544w0cOnQIX331FT766CNMmjQJACBJEqZOnYrXXnsNP/74I9LT0/Hggw8iLCwMw4cPB1A7sjV06FCMHz8e27dvx5YtWzB58mSMHj0aYWFhAID77rsPBoMB48aNQ0ZGBpYuXYr33nsP06dPl2uZMmUKfv75Z8ydOxf79+/Hyy+/jB07dmDy5Mke75e/4pz+03L6j4iIyLM8dDVig/3000+iZ8+ewmg0iq5du4qPPvrIZb/D4RAzZ84UwcHBwmg0iltuuUVkZ2e7tDl79qwYM2aM8PPzEyaTSTz88MOipKTEpc2ePXvE4MGDhdFoFG3bthVvvvnmBbUsW7ZMdOnSRRgMBtGjRw+xatWqer2Wul6SeSXS//hRiJdM4ugrPa7aOYiIiJqTur5/S0IIoXSway6sVisCAgJgsVhgMpmuyjmyUn5BtzWjkCeFIfylrKtyDiIiouakru/fjXr6j+pPck7/gWuqiIiIPImhSmW0Wi5UJyIiUgJDlcpoOFJFRESkCIYqldHqaz9qR8dQRURE5FEMVSrDkSoiIiJlMFSpjPbczT+1XFNFRETkUQxVKqPV1U7/caSKiIjIsxiqVMY5UsU1VURERJ7FUKUyzjVVOskB4XAoXA0REVHzwVClMjq9Uf7abufn/xEREXkKQ5XKaHU6+WtbTbWClRARETUvDFUqozu3pgoAbLYaBSshIiJqXhiqVEZ37uafAGC3cfqPiIjIUxiqVEarPX/6r0rBSoiIiJoXhiqVkTQa2ETtj9XBhepEREQew1ClQnZoa//kmioiIiKPYahSIZscqnj1HxERkacwVKmQXeJIFRERkacxVKmQc/qPa6qIiIg8h6FKhf6c/mOoIiIi8hSGKhWSR6q4poqIiMhjGKpUyOFcU2XnmioiIiJPYahSIedIleCaKiIiIo9hqFKhP6/+4/QfERGRpzBUqZCDI1VEREQex1ClQnap9vP/eEsFIiIiz2GoUiHnQnXBm38SERF5DEOVCsmhysFQRURE5CkMVSrkDFWc/iMiIvIchioVcpxbU8XpPyIiIs9hqFIh4QxVDo5UEREReQpDlQrJa6o4/UdEROQxDFUqJDTnRqr4MTVEREQew1ClQuLcSBU4/UdEROQxDFUq5OCaKiIiIo9jqFIh5/QfR6qIiIg8h6FKhYS8UJ1rqoiIiDyFoUqF/hypsitbCBERUTPCUKVGnP4jIiLyOIYqFZJHqjj9R0RE5DEMVWp0bk2VxJEqIiIij2GoUiGh0Z/7gmuqiIiIPIWhSo20tdN/Eqf/iIiIPIahSo2ca6o4UkVEROQxDFVqpOGaKiIiIk9jqFIh6dyaKoYqIiIiz2GoUiPnmirBUEVEROQpDFVqpHGGKq6pIiIi8hSGKhWStM7pP4YqIiIiT2GoUiFJw+k/IiIiT2OoUqNza6o0DFVEREQew1ClQhrn9B/XVBEREXkMQ5UanRup0vKWCkRERB7DUKVCGl79R0RE5HEMVSrkvPpPw1BFRETkMQxVKqTRnZv+A6f/iIiIPIWhSoWcH1PDkSoiIiLPYahSIY18SwWGKiIiIk9hqFIhjc4AgNN/REREnsRQpUIcqSIiIvI8hioV0uhq11RpGaqIiIg8hqFKhZx3VNeCoYqIiMhTmlSoevPNNyFJEqZOnSpvq6ysxKRJk9CyZUv4+flh5MiRyM/Pd3lebm4uhg0bBh8fH7Rp0wYzZsyAzea63mjjxo3o168fjEYjOnXqhMWLF19w/gULFqBDhw7w8vJCbGwstm/ffjVe5hXTyrdUYKgiIiLylCYTqlJTU/Hhhx+iV69eLtunTZuGn376CcuXL8emTZtw8uRJjBgxQt5vt9sxbNgwVFdXY+vWrfj888+xePFizJo1S25z9OhRDBs2DDfffDN2796NqVOn4tFHH8Uvv/wit1m6dCmmT5+Ol156CTt37kTv3r2RkJCAgoKCq//i64kjVURERAoQTUBJSYno3LmzWLt2rbjxxhvFlClThBBCFBcXC71eL5YvXy63zcrKEgBEcnKyEEKI1atXC41GI8xms9xm4cKFwmQyiaqqKiGEEE8//bTo0aOHyznvvfdekZCQIH8/YMAAMWnSJPl7u90uwsLCRFJSUp1fh8ViEQCExWKp+4tvgLyD6UK8ZBLWWcFX9TxERETNQV3fv5vESNWkSZMwbNgwxMfHu2xPS0tDTU2Ny/auXbsiIiICycnJAIDk5GRER0cjODhYbpOQkACr1YqMjAy5zf8/dkJCgnyM6upqpKWlubTRaDSIj4+X21xMVVUVrFary8MTnAvVdRypIiIi8hid0gVczpIlS7Bz506kpqZesM9sNsNgMCAwMNBle3BwMMxms9zm/EDl3O/c91dtrFYrKioqUFRUBLvdftE2+/fvv2TtSUlJeOWVV+r2Qt2Ia6qIiIg8r1GPVOXl5WHKlCn48ssv4eXlpXQ59fbcc8/BYrHIj7y8PI+cVyuPVDk8cj4iIiJq5KEqLS0NBQUF6NevH3Q6HXQ6HTZt2oR58+ZBp9MhODgY1dXVKC4udnlefn4+QkJCAAAhISEXXA3o/P5ybUwmE7y9vdGqVStotdqLtnEe42KMRiNMJpPLwxN05+6orpEE7DbeVZ2IiMgTGnWouuWWW5Ceno7du3fLj5iYGCQmJspf6/V6rFu3Tn5OdnY2cnNzERcXBwCIi4tDenq6y1V6a9euhclkQvfu3eU25x/D2cZ5DIPBgP79+7u0cTgcWLdundymMXGuqQIAm61awUqIiIiaj0a9psrf3x89e/Z02ebr64uWLVvK28eNG4fp06ejRYsWMJlM+Oc//4m4uDhcd911AIAhQ4age/fueOCBBzB79myYzWa8+OKLmDRpEoxGIwDg8ccfx/z58/H000/jkUcewfr167Fs2TKsWrVKPu/06dMxduxYxMTEYMCAAXj33XdRVlaGhx9+2EO9UXcG459TpWXWIhi9fBSshoiIqHlo1KGqLt555x1oNBqMHDkSVVVVSEhIwAcffCDv12q1WLlyJSZOnIi4uDj4+vpi7Nix+Ne//iW3iYyMxKpVqzBt2jS89957aNeuHT755BMkJCTIbe69916cPn0as2bNgtlsRp8+ffDzzz9fsHi9MfDy9sUJKRhtRT5OZu9AizZtlS6JiIhI9SQhhFC6iObCarUiICAAFovlqq+v2jnnTvQr24xtnabiuvs9fwUiERGRWtT1/btRr6mihqtq3QMAoCvYp3AlREREzQNDlUr5tO8PAGhdmq1wJURERM0DQ5VKte0WCwAItx9HealF4WqIiIjUj6FKpVqFROAMAqGRBHKzLrwbPREREbkXQ5WKnfDqDACwHElTuBIiIiL1Y6hSsfKWtYvVJfNehSshIiJSP4YqFTO26wMACLJe+kOfiYiIyD0YqlQsOGoAAKC97RhqqqsUroaIiEjdGKpULKxDN1jhA4NkQ272LqXLISIiUjWGKhWTNBrkGToCAM4e4hWAREREVxNDlcqVBHYHADhO7lG4EiIiInVjqFI5bVhvAICpOEvhSoiIiNSNoUrlWnWOAQBEVB+Gw25XuBoiIiL1YqhSuXad+6BK6OEnVeDkUY5WERERXS0MVSqnNxiRq+8AAMg/wMXqREREVwtDVTNQaOoGAKg+vlPhSoiIiNSLoao5COkFAPAtzFS4ECIiIvViqGoGAq/pDwBoW3kQwuFQuBoiIiJ1YqhqBiK6XQu7kNASFpwx5ypdDhERkSoxVDUD3r7+yNO2AwCc3L9N4WqIiIjUiaGqmTjjFwUAKM/hZwASERFdDQxVzYS97bUAgNbH13JdFRER0VXAUNVMRN3yEKqEHp3sh3Fw9+9Kl0NERKQ6DFXNRGCrEKQH3AgAKP79Q4WrISIiUh+GqmbEJ+5RAEDPwt9QYilUuBoiIiJ1YahqRrrFJiBHEw4fqQqZv3yidDlERESqwlDVjEgaDU51uhcA0Cr7Ky5YJyIiciOGqmamW8IEVAk9OtqP4sDOjUqXQ0REpBoMVc1MQMtg7A28GQBg+eNjhashIiJSD4aqZsh/4HgAQHTRb7AUnVG4GiIiInVgqGqGoq6NxzFNBLylauz/haNVRERE7sBQ1QxJGg3MnccAANoc+JoL1omIiNyAoaqZ6jZ0AiqEAZGOHKQsTVK6HCIioiaPoaqZCghqhT1RTwAAYvb/GxlbVytcERERUdPGUNWMxY5+ATtM8dBJDoT++hjMuQeVLomIiKjJYqhqxiSNBj0eW4zD2mvQAlaUfD4aleWlSpdFRETUJDFUNXPevv7wfmAJiuCPzvZDSP/wEZeF68LhgMNuV7BCIiKipkESQgili2gurFYrAgICYLFYYDKZlC7Hxb7ff0C338ZCKwmY0Rp6VMNbVMIL1SiUAlD90K8I6xCldJlEREQeV9f3b45UEQCg5/V3IbXLdABACE6jJSzwkaqgkQRaoRi5q+cqXCEREVHjxpEqD2rMI1VOh/Zsga26AgZvfxh9/GDevw39t09HifCG5qn98PUPVLpEIiIij6rr+7fOgzVRE9Cp9yCX70Pbd0Ve6r8RjpNIWf0hYu99RqHKiIiIGjdO/9Ff0mi1ONHlAQBASPYXvPs6ERHRJTBU0WX1uP1xlAkvtHccx74/flC6HCIiokaJoYouyz+gBfa1uQMAYE9epHA1REREjRNDFdVJ2JDaj7TpVZ6CE0eyFK6GiIio8WGoojoJ79wbe72uhUYSyPvlPaXLISIianQYqqjOxIAJAIDu+T+grKRY2WKIiIgaGYYqqrPoG0fiuBQKE8qxb83HSpdDRETUqDBUUZ1ptFoc73w/ACAy8wOcMecqXBEREVHjwVBF9dLrb/9EjiYcbVCIM5+MQlVludIlERERNQoMVVQvPn4B0Nz3NazwRVdbFvYsGscbghIREYGhihogvFM0cm6eD7uQMKB4NVKWJildEhFdAVtNNdJWfYKTx7KVLqVJSZn/MLJfG4DiM2alS6FGgqGKGiT6xhFI7TINABCz/9/Y9/ul77ReXVWJ5M+fx4HXrsWe9Us8VeJVwynPpq+irATpm76DraZa6VKuun1bfkLOv3oi+bNnLjqqbKupxp5596J/6pMwLr4VJ4/uV6DKpmf/9rWIPfMdomzZ2L/8ZaXLoUaCoYoaLHbMTKQGDIFOciB83USkLH0LlqIzLm2yUn7BybdiEHd0AbrYDqDnpsex/dt3FKnXYbdf8TG2f/su9Elh2PblK26oiJRgt9lw7N0ERG94GHvm3euWvxeN1bGsHWj/63i0d+QhLmcRUt9/wCVI2m027H7/PvQvWQ8AaAkLav77d1gKTytVcpNhW/ea/HVf8zfIP35YwWqosWCoogaTNBpEP74YB3RdEIAyxGa9AeO7XbHj7ZHYu/FbbJ93P7qtGYUOjjwUwoTd3tdBKwkMSH8ZyZ8+7bG1WNVVlUh9ZxQq/xWK5E+moaKspEHHycnejV57X4NGEuh74H2cOJLh5krJE7b/70V0q6n92fUvWY+Uz55SuKKr44w5D8alo+EvVSBPCqudri9aifR37kJleSkcdjt2zr8fMda1qBFapHR/EQVogfaOPBxfNBLVVZVKvwS3cffvmoytq9GzajeqhRaHtdfAKNUg59tZbj0HNU0MVXRFvLx90XbKWmzr8hSOatrDS6pBjPU39Nr4CAYU/gQA2B50B7T/3IHeM9Ygue3DAIC43A+xff7YS06/CIcDRadP4dCeLTh+aF+D66ssL0XWu3fiWssv8JGqEHf8UxT9ux92r6vfNGR1VSWql42Dl1QDu5BglGpwZvlULtJvYg7s3ISYox8BANL8bwYAxB3/FKnfz1eyrIuy1VSj4MTRBj23oqwEhZ+MQChOI08Kg/+kDdg7aD6qhB59y7fi6Du3Iu39RFxbvAY2oUH6dXMRO2oGSkZ+jTLhhR7Ve7Bn4UNN/u+35Ww+drw9EsX/isDeDd+45ZjC4YC04XUAwK5Wd6Jm6BwAQP/CVcjJ3u2Wc9CFTp88hvRN3zX6kWVJCCGULqK5sFqtCAgIgMVigclkUroctxMOBw7u3oyiP/6DqML1OKttg6pbk9D9uqEu7VKWzca1GW/UfuSNFIZyrT8ckhYOSQsJgH/NWbRynIG39GfgytJ3R1mvhxB96wMwevnUqZ4SSyHyFvwN3avTUSEM2N3hEVyTsxzBOAsA2OUzECH3vovQ9lGXPVbyx1MRd+IzWOCLvFs/RJdfH4JBsmFn3Hz0S3ig7p3kAbaaahzavRkdelwHLx+/q36+4jNmFORmo6aiFLaqEtgqSqHR6dHthr/Dy9v3qp+/rspKilH4dhzCxUmk+d2EftNXYNsnUxF38nNUCy0ODvkvegwapmiNleWl2L/lR9Ts+wGdLX8gEKVIaf139J+wEDq9oU7HcNjt2P32cPQr24xi+KHk/p8R3ikaAJC57We0+/kRmFAGALALCbsGzEHMsPHy8/dsWI4eGydAJzmQ3P5xxD38lvtfqAfsWb8EbTc/g1YoBgAUwQT7hD/QKqz9FR03ffMPiF7/IKqEHpYJqWjTNhK7Zt+GvuVbsdPvBvR76ic3VE/n27flJ4SvfQwBKEOGIRqBoz9E22t6eLSGur5/M1R5kNpDVX3s/OW/6LF1GoxSzV+2O4sAmEQp9FLt/06KYEJ2yJ1AQDugqhSiugSa6jIIjRaa4O4IuqY/wqP6oaKsBGc+vBOdbQdRIryRd9tidL9uKMpKipH+5fPof2oJ9JIdJcIbB69LQr/bHr5kDfu3r0XnVfdAKwmkDXgX/W9/GMmfTEPc8U9hRiv4P5kGX//ASz6/vNSCY/uSYa8qR9R1t8Ng9GpQn9VFqbUIRz74O3pV7sBpBOFIt8fR564n6hxE6yv1+wXoteuli/4cj2kiYLtrITr1HnxVzn3GnIvDm5fAeKx2PVCVV2s4fNtA4x8Cr9Yd0PnaIfDxC5Dbb593PwYU/oQCtIDxn9sQ0DIYDrsdu94Zgf6lG2GBLyz3rUZElz51On9NdRUO79qE4oNbIRn94d26AwJCO6JNu47w9vWv12s5cSQDp76fhe6W3+EjVV2wP93YFxGPLUdAi9Z/eZwSSyEyv5iG2LPfo1rocOi2Ly/4T83RzFT4LhuFlqIIu/onIeZvEy84TsqyOYjNrF0ztMN0K9qP/jdah3Wo12tyKj5jxsHNSxF53fA6Bxpr8Vkc/OQRdC3ZBi3s0EBAQu1b1X6v3tDc8BS6x90GSXPhZEuJpRBZn03CgOLVAIAcTTsISOjgyMNer/7oOWMtNFptg16LcDhw4I04RNn2Y1ubUbjuH7WfLHE0MxXtl94KjSRw8K6f0LnvDQ06fkOcMefiRFYKynPSYDy9D/6Vp3C2/e249r6XoNXpPFYHAKSt+gQBOz/A2a73YcDI6Rf9+VSUlWD/H9+hXfSNdfo7lbL83+i37w35PQAAKoQBe6KewLWjnvPYa2SoaoQYqlzlHz8M84E0CLsNDocdwm4DhB1egaEIDL0GrcLaw+jlgzMnc3Dwlw/QMWcZ2qDwsse1CwllkjdMKEcRTDh799cXvLEfy9qBym8no6stCwCQ0moEeo+bf8HISqm1CJZ3YtFW5CM1YAiunbYcQO2IQuGcfggT+UgOvR9xjy2Qn2MpPI0DG7+CyNuOVpZ9aG/PgVaq/WdWCBMOBA9D6M0T0L5rv3r11+mTx3Bs2bPoVPwH9rf9O/rc96rLm/cZcy6KPx6OTnbXBbOn0BrHe/0Tfe+cWOfRjsux1VRjxyf/xHX5tdOoZxCIMo0fqjXeqNZ4IbQ6By1gRY3QYkeH8bj2/lfrdW7hcOBwejJOp/0AQEDyMkHjHQidTyCqC3NhOrIaXaszoJEu/eurSuix37sPKiNvhaQzYkD6S3AICZm3foGeg/8mt6ssL0XO27cgyrYfZxGAg50fRe/h0y4ajPIO7sGJHSvhlbsZnct3w1e6+Lqj41IoTnQfj75/m/SXIbqspBh7v56F/ie+hEGyAQDMaIWc1jfBr88IVFkL0HXbM/CRqpAnhcEx+mu0j+pzwXGsxWeRsWI2uuf8FwHnRqF29HsLMX97/KLnLS+1wFpYgJCIzpesLfk/TyE29xNoJIFyYcSejo+h36jn6hXQc7LSoF82BmEiH6XCG/s6P4Z+9zz3l32Sd3APxNdjEOE48ZfH3q/vjqq4aeh1099x4kgmTu5ZC03OFlxjTUELWOEQEraHjEafsf9Gfk42gpckwEuqwbbOT+K6RNf1T2mrP4Nhzxeo1ptQHdAB2ladYAqLQmjnvi5Bds/6Zei9eTwqhAFlE9PQKiRC3pf6zihca/kF6cZ+iH5uw2X7prqqEjlZqSg8sA3SyZ3wqTiJMt8IiFZR8G0XjZBOvdEqJOKCYOKcETibuhzh5nVoJ05d9PhZ+h4wjfkP2l7T7bK1uMPOnxejd/JU+XfdLp9BiHzkUwS2CpHb7F77FYK3zEIoTqNaaLEnaAhaDXkSkd2vveB4tppq7PjoH7judO3v3B3+t6D17S+gdMU09KjeA6D274DtpucR2ev6v/yPrTswVDVCDFVXxlZTjfQNy2BP/w6SsMOu94VD7wth8INUUwHf4v1oV3UYQbACAArQAhWjv71keKmprsKOxU8h7uQXAIBD2o7wGvMFAtu0xanD6bDkZUKf9R16V6TAjNbwmZoCU2BL+fm71y1Bn98fQ43Q4vi9v6CsyIzKlMWItmy6YOSmAC2ggUOeigBqfyFYOt+NawaP+sv/sVWWl2L3sjfQ6+gnLqMYZrTGqYEvo0/8fTh+OB3ar+5BmMhHEUww3/YJrMd245qshWiNIgDAaQQhz68XqsOuRVCXQYiMHtigUTNL4WnkfjgK0VU7AQDJ4Y8i9qHZLv/7Lyw4gWOfP45+ZZsBAAd0XVA2YAoAwF5TAUd1JeCwwRAYioDQjmjdrhP8TEE4Y87DoXWfIvjwd4h0HLtsLdm6KBRFJEDyDoSjxAxNWQEMFacRXHEIYSL/gvbbQhJx3eMfXLD9bP5xlH44FO0debXfIwAHOz2M6Lum4dSRfTid+i1CT65Fh3P7nYrgj2O+vaFxVCOgyozW9gKXoHVSaoMT0ZMvCLR2mw27Vn+CiJ1vyf9RSDf2g+HWmejS7yaXN9LD6dvg++39CMFpWOGDzE4TIBlNtW00WjjOHkP340vkKb1cTVucjX0GfRPGXrb/Lufgrs1wrJqBKFvtbRaOS6E43voGaGrKoLWVQ2crg5A0sPe8B32GjHUZNUjf9B06rP8H/KUKVAudHBrzpDAU3fAqet389wvOt3fDN+iw6Z8woRz5aIkzQ+ajRduOkDRaaDRaVFgLYf5tHvqcWSX/GysR3vCXKlyOc1IKRvGQ99A97jZ5W8qy2YjNfB3VQoe8kT+hY6+BsJzNx6HFj8tXP/5/DiHhmLY9TrfoD33H6+G/Yz462w9d9O/RyWPZaPVZHAySHckREyAZ/SGqy4Cacmiqy6CpKYG+pgQGWym8bSVoaz8u98mllAsjzmhbwaJvgwrvUAitAe3P/oEQ/HmVtUNIyNO2w2m/KNiCewGSBtHZ8+ErVaJMeCGz9/OIGf7Pi44aucueDcvRbeNjMEh2ZOp7olN1FgySHQVogYL499CibRcULJuCPhXbAABlwsvl38ler2tRGXUXhK0aosoKVJbAv2A7elSnAwCSO0zEdQ++AUmjgcNuR+p376DHvn/D79zP3S4k5Grb43RAD6BtDNr2u83tYZKhqhFiqLr6hMOBM+ZcmA/tQVhUf7QMbnfZ5+zZsBwRm6YhCCWwCQ10kuviXIeQkJXwFXoMvP2C5+6afTv6lm9BtdDCcN7w9BFNB+SH3AivDgPQtscgtGkbCVtNNfZt+hZi5xeILtvmcp5sXRQKw29Fy+hb4bDbUFNRgpqKUtQUn0RE1scIxelz7bqiuPMItM/6GCHntqUb+6Fd1UEEoQTHpRAg8Vu069QTwLlAtmIuog5+IodNpyqhR762DSz6YFR4h8BuageNXxtodAZAq4dGZ4BGp4fDVgNHTSUc1RUQNRVod+grtBOnUC6M2B83G/2GPnTJn0Xayo/QZee/5Df8v1IMP/iJcrlfqoUO+/ziUGMMgq6mBPqaUhhspbBpjShtfys6XD8aIeGdLnnu3OxdOJn6PQLzfkOX6iwc0ndBh6c2XnKkpbqqErt/+gDtMhYiTBQAAGqE1mXaoUZoke0VjdK2N6BV7wRc0zPOJUwKhwOWwgLs//UTdDrwsRyij0shOOsVAd/qswi0n0WQsMj/oz8hBaMgbhb6xN93yTe+s/nHUfDJKPmqxYvJ0YTjdL8n0HfoI26dEnHY7Uhb+SEid73l8p+C/692dO5R9L5jIvb8OB/9M9+ETnIgS98DrcctxZHkFei4599oCQuA2r/zVt9I2EztoAuKgK34OAbkfAytJJCl747W45ahVUj4Rc915mQODv2QhF7m7+AjVaFaaHHI0A3W4Fj4db0JnWPiL/g5C4cDu/89DH3LtyJHE47C655Fu60vojWKYBMa7AgdA/gHQyo8At/SY2hVdUL+N3a+cmFE5aRdaNGm7QX7UhaMQ+zpui+It8AXOV5dUdayF7StroH9zBF4FR1Aq4qjCHOckv+OXKyGLP84oPtwRA0eDj9TkMv+k0f3w/LVI/Lfl4O6zqjS+kLjsEEraqARdpQbWqLCvz2klh3hHdwZBm9/WHL3AvkZMFn2I6wmB4Wa1jCH3oyW/YejU+/rLzptmrFlFTr+OhZeUg3S/G9Gnynf4GhGCgw/jEeE4wQcQkINdDBKNbUj12GJ6J34GnL370D5hnfRp/T3S444/9XvGHPuQeR9+zzCLTtdQiYAbOs0Fdfd797b3jBUNUIMVY1X/vHDKPz8AfmX0BkEosAQjlK/DvDqdTd63TTyos8z5x6E6T+D4CNVoVR4I6PVELQY/Cg69R78l/8zPHMyB4fW/QeBOb/KU5B/WR9aIq//M+g/bDwkjQblpRbs+XoW+h//rxzmDuo6o8X47y8aJCvLS3Fo1waUHkyGV34a2ldkIAgNu7UEUDsCUznyf7imZ+xl2xacOIrcJU8isPwYbBojbBoD7BoDBDTwqz6N1nazPGUF1L7ZFne5B13jH7rsGqK6KisphsHoDb3BeNm2NdVV2LXqQ4TtXYB2wlz7i91vABxRd6Dz9X9HQFCrOp2zoqwEe1bMRdSh/1wQaAGgVHgj/ZpH0HfUC3Va0F9dVYm0L2fBeDYTknBAggOScNRe5NFjJPokPHRV15eUWouw74d3IMrPAgY/SEZ/aIx+cBTlouvxpQhEKQDACh+YUHuD3NSABPSauFgOONbis8j8+gX0Ny9zCavn2x50B3o/9nGdphktZ/ORn5OF8Kj+dVrHVnT6FGwL4uTRW6B25KzizoXo0u+mC9qfMechd9dvqDn8O9oUpiHCnoPUzlMu+YZtOZuPg5//A1pbOexabzh03nDofSD0vvIUttYnAHqfQLSM6IqwDt0u+XuisqIMZ04cRXH+UVSczoWtOA9SRTGMHQej2+Dhl70IxW6zYftXr6D/4QUu/+FrqNMIwtHAODgCI6EJCIV3i7awV1eiyx9T4SNVYbdPHHpM/UH+N1ZeakH6p5MRW/gjACDD0Bt+I969YObgxJEM5K15B/6WA6jW+cKm94ND7weHMQChg+9Hh24xl63tzMkc5O37HZU5qfA/sxu6W2eha8wtV/yaz6eKUJWUlITvvvsO+/fvh7e3NwYOHIi33noLUVF/Xq1VWVmJJ598EkuWLEFVVRUSEhLwwQcfIDg4WG6Tm5uLiRMnYsOGDfDz88PYsWORlJQE3Xm/gDZu3Ijp06cjIyMD4eHhePHFF/HQQw+51LNgwQLMmTMHZrMZvXv3xvvvv48BAwbU+fUwVDVuDrsdJ45mwtQytM5vnABwcPfvsJ48gG43/N1lYXRdnTmZg8NblsP78BqEVR5CtWREpeSNaq0PqrU+KA+JRe97nrvkGp/TP8yEXeuN7o9+WOd1BcLhwMlj2Sg6eRAVZ3JhK8qDtuQE9FVFkBw2aEQNtI4aaIQNDkkHu8YIu9YIu8YIm28IokbORFDr0Hq/1kspsRTidN5BGH1MHlsDcjm2mmrkHdiFkA7d673w/HxlJcXI+O0LwOGAMSgEvi3bIbB1OILatPX4QuKrpbzUgr0/zUeH7M/k0Z3kyMm47oFXLxoaThzJwql9G1FTmAOt9Ti8yk/Cy1aCoqh7L7nA2V2cV+8BwLbW96D3Q+/U+efrsNsbvMhdKXkH98Cc8TskefTZCGg0qCo8DnH2CIzWYwiqzIOXoxwFXpEoC+oGfVhPBEb0RHHOXmgOrEFUScol1w8CwD5jH3Sauvqi/znY98ePsFWVo/fNo67qz/VqU0WoGjp0KEaPHo1rr70WNpsNzz//PPbt24fMzEz4+tb+8CZOnIhVq1Zh8eLFCAgIwOTJk6HRaLBlyxYAgN1uR58+fRASEoI5c+bg1KlTePDBBzF+/Hi88cYbAICjR4+iZ8+eePzxx/Hoo49i3bp1mDp1KlatWoWEhAQAwNKlS/Hggw9i0aJFiI2Nxbvvvovly5cjOzsbbdq0qdPrYagiIjWrqa5C+vqv4RUQ7LKeqbHZv30ttAYvdO5zvdKlNAlVleXI3rYGZQd/h7YsH16VBfCvPoNARyGO+vZB14n/a9B/KJuSOr9/iyakoKBAABCbNm0SQghRXFws9Hq9WL58udwmKytLABDJyclCCCFWr14tNBqNMJvNcpuFCxcKk8kkqqqqhBBCPP3006JHjx4u57r33ntFQkKC/P2AAQPEpEmT5O/tdrsICwsTSUlJda7fYrEIAMJisdTjVRMREZGS6vr+3aTG4iyW2gWOLVq0AACkpaWhpqYG8fHxcpuuXbsiIiICycnJAIDk5GRER0e7TAcmJCTAarUiIyNDbnP+MZxtnMeorq5GWlqaSxuNRoP4+Hi5zcVUVVXBarW6PIiIiEidmkyocjgcmDp1KgYNGoSePWuvbDKbzTAYDAgMDHRpGxwcDLPZLLc5P1A59zv3/VUbq9WKiooKnDlzBna7/aJtnMe4mKSkJAQEBMiP8PCLX8lCRERETV+TCVWTJk3Cvn37sGRJ/T6zTUnPPfccLBaL/MjLy7v8k4iIiKhJahKXnkyePBkrV67E5s2b0a7dn5eLh4SEoLq6GsXFxS6jVfn5+QgJCZHbbN++3eV4+fn58j7nn85t57cxmUzw9vaGVquFVqu9aBvnMS7GaDTCaLz8JdxERETU9DXqkSohBCZPnowVK1Zg/fr1iIyMdNnfv39/6PV6rFu3Tt6WnZ2N3NxcxMXFAQDi4uKQnp6OgoICuc3atWthMpnQvXt3uc35x3C2cR7DYDCgf//+Lm0cDgfWrVsntyEiIqJmzjPr5htm4sSJIiAgQGzcuFGcOnVKfpSXl8ttHn/8cRERESHWr18vduzYIeLi4kRcXJy832aziZ49e4ohQ4aI3bt3i59//lm0bt1aPPfcc3KbI0eOCB8fHzFjxgyRlZUlFixYILRarfj555/lNkuWLBFGo1EsXrxYZGZmigkTJojAwECXqwovh1f/ERERNT11ff9u1KEKwEUfn332mdymoqJC/OMf/xBBQUHCx8dH3H333eLUqVMuxzl27Ji47bbbhLe3t2jVqpV48sknRU1NjUubDRs2iD59+giDwSCuueYal3M4vf/++yIiIkIYDAYxYMAAsW3btnq9HoYqIiKipqeu79+N+uafasObfxIRETU9dX3/btRrqoiIiIiaCoYqIiIiIjdgqCIiIiJyA4YqIiIiIjdgqCIiIiJyA4YqIiIiIjdoEh9ToxbOu1dYrVaFKyEiIqK6cr5vX+4uVAxVHlRSUgIACA8PV7gSIiIiqq+SkhIEBARccj9v/ulBDocDJ0+ehL+/PyRJcttxrVYrwsPDkZeXx5uKegD723PY157DvvYc9rXnuKuvhRAoKSlBWFgYNJpLr5ziSJUHaTQatGvX7qod32Qy8R+oB7G/PYd97Tnsa89hX3uOO/r6r0aonLhQnYiIiMgNGKqIiIiI3IChSgWMRiNeeuklGI1GpUtpFtjfnsO+9hz2teewrz3H033NhepEREREbsCRKiIiIiI3YKgiIiIicgOGKiIiIiI3YKgiIiIicgOGKhVYsGABOnToAC8vL8TGxmL79u1Kl9TkJSUl4dprr4W/vz/atGmD4cOHIzs726VNZWUlJk2ahJYtW8LPzw8jR45Efn6+QhWrx5tvvglJkjB16lR5G/vafU6cOIH7778fLVu2hLe3N6Kjo7Fjxw55vxACs2bNQmhoKLy9vREfH4+DBw8qWHHTZLfbMXPmTERGRsLb2xsdO3bEq6++6vLZcezrhtm8eTPuvPNOhIWFQZIkfP/99y7769KvhYWFSExMhMlkQmBgIMaNG4fS0tIrro2hqolbunQppk+fjpdeegk7d+5E7969kZCQgIKCAqVLa9I2bdqESZMmYdu2bVi7di1qamowZMgQlJWVyW2mTZuGn376CcuXL8emTZtw8uRJjBgxQsGqm77U1FR8+OGH6NWrl8t29rV7FBUVYdCgQdDr9VizZg0yMzMxd+5cBAUFyW1mz56NefPmYdGiRUhJSYGvry8SEhJQWVmpYOVNz1tvvYWFCxdi/vz5yMrKwltvvYXZs2fj/fffl9uwrxumrKwMvXv3xoIFCy66vy79mpiYiIyMDKxduxYrV67E5s2bMWHChCsvTlCTNmDAADFp0iT5e7vdLsLCwkRSUpKCValPQUGBACA2bdokhBCiuLhY6PV6sXz5crlNVlaWACCSk5OVKrNJKykpEZ07dxZr164VN954o5gyZYoQgn3tTs8884wYPHjwJfc7HA4REhIi5syZI28rLi4WRqNRfP31154oUTWGDRsmHnnkEZdtI0aMEImJiUII9rW7ABArVqyQv69Lv2ZmZgoAIjU1VW6zZs0aIUmSOHHixBXVw5GqJqy6uhppaWmIj4+Xt2k0GsTHxyM5OVnBytTHYrEAAFq0aAEASEtLQ01NjUvfd+3aFREREez7Bpo0aRKGDRvm0qcA+9qdfvzxR8TExOCee+5BmzZt0LdvX3z88cfy/qNHj8JsNrv0dUBAAGJjY9nX9TRw4ECsW7cOBw4cAADs2bMHf/zxB2677TYA7OurpS79mpycjMDAQMTExMht4uPjodFokJKSckXn5wcqN2FnzpyB3W5HcHCwy/bg4GDs379foarUx+FwYOrUqRg0aBB69uwJADCbzTAYDAgMDHRpGxwcDLPZrECVTduSJUuwc+dOpKamXrCPfe0+R44cwcKFCzF9+nQ8//zzSE1NxRNPPAGDwYCxY8fK/Xmx3yns6/p59tlnYbVa0bVrV2i1Wtjtdrz++utITEwEAPb1VVKXfjWbzWjTpo3Lfp1OhxYtWlxx3zNUEV3GpEmTsG/fPvzxxx9Kl6JKeXl5mDJlCtauXQsvLy+ly1E1h8OBmJgYvPHGGwCAvn37Yt++fVi0aBHGjh2rcHXqsmzZMnz55Zf46quv0KNHD+zevRtTp05FWFgY+1rFOP3XhLVq1QparfaCq6Dy8/MREhKiUFXqMnnyZKxcuRIbNmxAu3bt5O0hISGorq5GcXGxS3v2ff2lpaWhoKAA/fr1g06ng06nw6ZNmzBv3jzodDoEBwezr90kNDQU3bt3d9nWrVs35ObmAoDcn/ydcuVmzJiBZ599FqNHj0Z0dDQeeOABTJs2DUlJSQDY11dLXfo1JCTkgou5bDYbCgsLr7jvGaqaMIPBgP79+2PdunXyNofDgXXr1iEuLk7Bypo+IQQmT56MFStWYP369YiMjHTZ379/f+j1epe+z87ORm5uLvu+nm655Rakp6dj9+7d8iMmJgaJiYny1+xr9xg0aNAFtwY5cOAA2rdvDwCIjIxESEiIS19brVakpKSwr+upvLwcGo3rW6xWq4XD4QDAvr5a6tKvcXFxKC4uRlpamtxm/fr1cDgciI2NvbICrmiZOyluyZIlwmg0isWLF4vMzEwxYcIEERgYKMxms9KlNWkTJ04UAQEBYuPGjeLUqVPyo7y8XG7z+OOPi4iICLF+/XqxY8cOERcXJ+Li4hSsWj3Ov/pPCPa1u2zfvl3odDrx+uuvi4MHD4ovv/xS+Pj4iP/9739ymzfffFMEBgaKH374Qezdu1fcddddIjIyUlRUVChYedMzduxY0bZtW7Fy5Upx9OhR8d1334lWrVqJp59+Wm7Dvm6YkpISsWvXLrFr1y4BQLz99tti165dIicnRwhRt34dOnSo6Nu3r0hJSRF//PGH6Ny5sxgzZswV18ZQpQLvv/++iIiIEAaDQQwYMEBs27ZN6ZKaPAAXfXz22Wdym4qKCvGPf/xDBAUFCR8fH3H33XeLU6dOKVe0ivz/UMW+dp+ffvpJ9OzZUxiNRtG1a1fx0Ucfuex3OBxi5syZIjg4WBiNRnHLLbeI7OxshaptuqxWq5gyZYqIiIgQXl5e4pprrhEvvPCCqKqqktuwrxtmw4YNF/39PHbsWCFE3fr17NmzYsyYMcLPz0+YTCbx8MMPi5KSkiuuTRLivNu7EhEREVGDcE0VERERkRswVBERERG5AUMVERERkRswVBERERG5AUMVERERkRswVBERERG5AUMVERERkRswVBERERG5AUMVEZEHbdy4EZIkXfAB0UTU9DFUEREREbkBQxURERGRGzBUEVGz4nA4kJSUhMjISHh7e6N379745ptvAPw5Nbdq1Sr06tULXl5euO6667Bv3z6XY3z77bfo0aMHjEYjOnTogLlz57rsr6qqwjPPPIPw8HAYjUZ06tQJ//nPf1zapKWlISYmBj4+Phg4cCCys7PlfXv27MHNN98Mf39/mEwm9O/fHzt27LhKPUJE7sJQRUTNSlJSEr744gssWrQIGRkZmDZtGu6//35s2rRJbjNjxgzMnTsXqampaN26Ne68807U1NQAqA1Do0aNwujRo5Geno6XX34ZM2fOxOLFi+XnP/jgg/j6668xb948ZGVl4cMPP4Sfn59LHS+88ALmzp2LHTt2QKfT4ZFHHpH3JSYmol27dkhNTUVaWhqeffZZ6PX6q9sxRHTlBBFRM1FZWSl8fHzE1q1bXbaPGzdOjBkzRmzYsEEAEEuWLJH3nT17Vnh7e4ulS5cKIYS47777xK233ury/BkzZoju3bsLIYTIzs4WAMTatWsvWoPzHL/99pu8bdWqVQKAqKioEEII4e/vLxYvXnzlL5iIPIojVUTUbBw6dAjl5eW49dZb4efnJz+++OILHD58WG4XFxcnf92iRQtERUUhKysLAJCVlYVBgwa5HHfQoEE4ePAg7HY7du/eDa1WixtvvPEva+nVq5f8dWhoKACgoKAAADB9+nQ8+uijiI+Px5tvvulSGxE1XgxVRNRslJaWAgBWrVqF3bt3y4/MzEx5XdWV8vb2rlO786fzJEkCULveCwBefvllZGRkYNiwYVi/fj26d++OFStWuKU+Irp6GKqIqNno3r07jEYjcnNz0alTJ5dHeHi43G7btm3y10VFRThw4AC6desGAOjWrRu2bNnictwtW7agS5cu0Gq1iI6OhsPhcFmj1RBdunTBtGnT8Ouvv2LEiBH47LPPruh4RHT16ZQugIjIU/z9/fHUU09h2rRpcDgcGDx4MCwWC7Zs2QKTyYT27dsDAP71r3+hZcuWCA4OxgsvvIBWrVph+PDhAIAnn3wS1157LV599VXce++9SE5Oxvz58/HBBx8AADp06ICxY8fikUcewbx589C7d2/k5OSgoKAAo0aNumyNFRUVmDFjBv7+978jMjISx48fR2pqKkaOHHnV+oWI3ETpRV1ERJ7kcDjEu+++K6KiooRerxetW7cWCQkJYtOmTfIi8p9++kn06NFDGAwGMWDAALFnzx6XY3zzzTeie/fuQq/Xi4iICDFnzhyX/RUVFWLatGkiNDRUGAwG0alTJ/Hpp58KIf5cqF5UVCS337VrlwAgjh49KqqqqsTo0aNFeHi4MBgMIiwsTEyePFlexE5EjZckhBAK5zoiokZh48aNuPnmm1FUVITAwEClyyGiJoZrqoiIiIjcgKGKiIiIyA04/UdERETkBhypIiIiInIDhioiIiIiN2CoIiIiInIDhioiIiIiN2CoIiIiInIDhioiIiIiN2CoIiIiInIDhioiIiIiN/g/gM/fbBMtGOAAAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y_pred = housing_price_model.predict(X_test_normal)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "f4HovNNoupxU",
        "outputId": "03cd9148-553d-49b5-913f-8d17cb1350cf"
      },
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "46/46 [==============================] - 0s 2ms/step\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.DataFrame(y_pred, columns=[\"SalePrice\"])\n",
        "df.rename_axis('Id').to_csv(\"predictions.csv\")"
      ],
      "metadata": {
        "id": "2FzOvECpvFz6"
      },
      "execution_count": 62,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "v52bmfdwvxnx",
        "outputId": "39aa7880-6573-447a-c88c-668c0c751669"
      },
      "execution_count": 61,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       SalePrice\n",
              "0  116464.625000\n",
              "1  161027.171875\n",
              "2  169028.671875\n",
              "3  185950.656250\n",
              "4  199703.046875"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-b71a1f17-bca1-427a-bcc3-7fc632819206\" 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",
              "    }\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>SalePrice</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>116464.625000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>161027.171875</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>169028.671875</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>185950.656250</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>199703.046875</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-b71a1f17-bca1-427a-bcc3-7fc632819206')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </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-b71a1f17-bca1-427a-bcc3-7fc632819206 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-b71a1f17-bca1-427a-bcc3-7fc632819206');\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-e0ac0c6e-e688-4fbc-a237-fe7253ca6b9a\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-e0ac0c6e-e688-4fbc-a237-fe7253ca6b9a')\"\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-e0ac0c6e-e688-4fbc-a237-fe7253ca6b9a button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 61
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Note** -> Further data preprocessing is needed in order to submit the predictions to kaggle\n",
        "\n",
        "ToDO\n",
        "1. Handle Empty columns from predictions.\n",
        "2. More Feature Engineering.\n",
        "3. Improve the model.\n"
      ],
      "metadata": {
        "id": "fdam8x6mx9xs"
      }
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "J-bv6B-gww78"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}