MLP Titanic.ipynb

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        "<a href=\"https://colab.research.google.com/github/pbellot/FormationPANDAS/blob/master/MLP%20Titanic.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": true,
        "id": "cDHDWDlAbZmV"
      },
      "outputs": [],
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "from sklearn.model_selection import train_test_split"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "id": "j9CRFUKzbd6X",
        "outputId": "5e5abda3-7390-47ae-dbb9-76e8152febb4",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bd0ltvcDbZmX"
      },
      "source": [
        "### pour installer tensorflow\n",
        "voir les instructions données ici : https://github.com/jeffheaton/t81_558_deep_learning/tree/master/install\n",
        "liste des versions de tensorflow dans les différents channels : https://anaconda.org/search?q=tensorflow\n",
        "liste des versions de tensorflow officielles : https://www.tensorflow.org/install/source#tested_build_configurations\n",
        "avec tensorflow 2.11, il faut installer keras 2.3.1 et un python 3.7 à 3.10\n",
        "\n",
        "### documentation\n",
        "Keras : https://keras.io/"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "9Yp2bh7QbZma"
      },
      "outputs": [],
      "source": [
        "# Multilayer perceptron Neural Network\n",
        "from tensorflow import keras\n",
        "from keras.models import Sequential\n",
        "from keras.layers import Dense\n",
        "from sklearn import preprocessing\n",
        "from sklearn.preprocessing import MinMaxScaler\n",
        "from sklearn.preprocessing import StandardScaler\n",
        "from keras.utils.vis_utils import plot_model\n",
        "from keras.layers import Dropout\n",
        "from keras.utils import np_utils"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "TFuvklfcbZmb"
      },
      "outputs": [],
      "source": [
        "titanic = pd.read_csv(\"/content/drive/MyDrive/Analyse_donnees/titanic.csv\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "D4D3mGTwbZmc"
      },
      "outputs": [],
      "source": [
        "features = ['Pclass','Sex','Age','SibSp','Parch','Fare','Embarked']"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "e6O5B0R4bZmd"
      },
      "outputs": [],
      "source": [
        "titanic['Sex']=titanic['Sex'].map({'male':0,'female':1})\n",
        "titanic['Embarked']=titanic['Embarked'].map({'S':0,'C':1,'Q':2})\n",
        "titanic.dropna(subset=features,how=\"any\",inplace=True)"
      ]
    },
    {
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        "id": "K0Rn-kEybZme",
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              "     PassengerId  Survived  Pclass  \\\n",
              "0              1         0       3   \n",
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              "889          890         1       1   \n",
              "890          891         0       3   \n",
              "\n",
              "                                                  Name  Sex   Age  SibSp  \\\n",
              "0                              Braund, Mr. Owen Harris    0  22.0      1   \n",
              "1    Cumings, Mrs. John Bradley (Florence Briggs Th...    1  38.0      1   \n",
              "2                               Heikkinen, Miss. Laina    1  26.0      0   \n",
              "3         Futrelle, Mrs. Jacques Heath (Lily May Peel)    1  35.0      1   \n",
              "4                             Allen, Mr. William Henry    0  35.0      0   \n",
              "..                                                 ...  ...   ...    ...   \n",
              "885               Rice, Mrs. William (Margaret Norton)    1  39.0      0   \n",
              "886                              Montvila, Rev. Juozas    0  27.0      0   \n",
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              "889                              Behr, Mr. Karl Howell    0  26.0      0   \n",
              "890                                Dooley, Mr. Patrick    0  32.0      0   \n",
              "\n",
              "     Parch            Ticket     Fare Cabin  Embarked  \n",
              "0        0         A/5 21171   7.2500   NaN       0.0  \n",
              "1        0          PC 17599  71.2833   C85       1.0  \n",
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              "890      0            370376   7.7500   NaN       2.0  \n",
              "\n",
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          "metadata": {},
          "execution_count": 7
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      "source": [
        "titanic"
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    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "vFFKcDJRbZme"
      },
      "outputs": [],
      "source": [
        "model = Sequential()\n",
        "model.add(Dense(12, input_dim=7, activation='relu'))\n",
        "model.add(Dense(8, activation='relu'))\n",
        "model.add(Dense(1, activation='sigmoid'))"
      ]
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      "execution_count": null,
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          "base_uri": "https://localhost:8080/"
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      "outputs": [
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          "text": [
            "Model: \"sequential\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " dense (Dense)               (None, 12)                96        \n",
            "                                                                 \n",
            " dense_1 (Dense)             (None, 8)                 104       \n",
            "                                                                 \n",
            " dense_2 (Dense)             (None, 1)                 9         \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 209\n",
            "Trainable params: 209\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n"
          ]
        }
      ],
      "source": [
        "model.summary()"
      ]
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      "cell_type": "code",
      "execution_count": null,
      "outputs": [
        {
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",
            "text/plain": "<IPython.core.display.Image object>"
          },
          "execution_count": 13,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "plot_model(model, to_file='model_plot.png', show_shapes=True, show_layer_names=True)"
      ],
      "metadata": {
        "id": "J59vlSSIbZmg",
        "outputId": "0d5c6b1c-c3cc-4247-f414-2d1c96a93147"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "outputs": [
        {
          "data": {
            "image/png": "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",
            "text/plain": "<IPython.core.display.Image object>"
          },
          "execution_count": 14,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "plot_model(model, to_file='model_plot.png', show_shapes=False, show_layer_names=True)"
      ],
      "metadata": {
        "id": "Uxf3wadEbZmg",
        "outputId": "2eea9d94-bf27-474a-e505-28d99d2ec4c0"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "outputs": [
        {
          "ename": "ModuleNotFoundError",
          "evalue": "No module named 'visualkeras'",
          "output_type": "error",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
            "Cell \u001b[0;32mIn[15], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mvisualkeras\u001b[39;00m\n\u001b[1;32m      2\u001b[0m visualkeras\u001b[38;5;241m.\u001b[39mlayered_view(model, legend\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m, draw_volume\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\u001b[38;5;241m.\u001b[39mshow()\n",
            "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'visualkeras'"
          ]
        }
      ],
      "source": [
        "import visualkeras\n",
        "visualkeras.layered_view(model, legend=True, draw_volume=True).show()"
      ],
      "metadata": {
        "id": "etbeLNKnbZmh",
        "outputId": "6575dda4-1da8-4cd1-f73e-d7d217441490"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "outputs": [],
      "source": [
        "##### Réglage des paramètres d'apprentissage : (voir https://keras.io/api/optimizers/)\n",
        "opt = keras.optimizers.Adam(learning_rate=0.005)\n",
        "model.compile(loss='binary_crossentropy', optimizer=opt, metrics=['accuracy'])"
      ],
      "metadata": {
        "id": "nQqZR8G8bZmi"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "outputs": [],
      "source": [
        "def plot():\n",
        "    plt.figure(figsize=(17,14))\n",
        "    plt.rc('font', size=14)\n",
        "    plt.ylim(0.5,1)\n",
        "    plt.plot(history.history['accuracy'])\n",
        "    plt.plot(history.history['val_accuracy'])\n",
        "    plt.title('model accuracy')\n",
        "    plt.ylabel('accuracy')\n",
        "    plt.xlabel('epoch')\n",
        "    plt.legend(['train', 'test'], loc='upper left')\n",
        "    plt.show()\n",
        "    # summarize history for loss\n",
        "    plt.figure(figsize=(17,14))\n",
        "    plt.rc('font', size=14)\n",
        "    plt.plot(history.history['loss'])\n",
        "    plt.plot(history.history['val_loss'])\n",
        "    plt.title('model loss')\n",
        "    plt.ylabel('loss')\n",
        "    plt.xlabel('epoch')\n",
        "    plt.legend(['train', 'test'], loc='upper left')\n",
        "    plt.show()"
      ],
      "metadata": {
        "id": "MNvq_VL5bZmj"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "outputs": [],
      "source": [
        "X_train, X_test, Y_train, Y_test = train_test_split(titanic[features], titanic['Survived'], random_state=0)"
      ],
      "metadata": {
        "id": "smByh1pbbZmk"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/30\n",
            "54/54 [==============================] - 2s 10ms/step - loss: 4.5233 - accuracy: 0.5094 - val_loss: 0.8457 - val_accuracy: 0.6742\n",
            "Epoch 2/30\n",
            "54/54 [==============================] - 0s 3ms/step - loss: 0.7718 - accuracy: 0.6816 - val_loss: 0.6610 - val_accuracy: 0.6742\n",
            "Epoch 3/30\n",
            "54/54 [==============================] - 0s 4ms/step - loss: 0.6276 - accuracy: 0.6966 - val_loss: 0.6194 - val_accuracy: 0.6910\n",
            "Epoch 4/30\n",
            "54/54 [==============================] - 0s 4ms/step - loss: 0.5716 - accuracy: 0.7079 - val_loss: 0.6306 - val_accuracy: 0.6854\n",
            "Epoch 5/30\n",
            "54/54 [==============================] - 0s 4ms/step - loss: 0.5743 - accuracy: 0.7247 - val_loss: 0.6700 - val_accuracy: 0.6910\n",
            "Epoch 6/30\n",
            "54/54 [==============================] - 0s 4ms/step - loss: 0.5865 - accuracy: 0.7135 - val_loss: 0.6373 - val_accuracy: 0.7079\n",
            "Epoch 7/30\n",
            "54/54 [==============================] - 0s 3ms/step - loss: 0.6069 - accuracy: 0.7247 - val_loss: 0.6175 - val_accuracy: 0.7303\n",
            "Epoch 8/30\n",
            "54/54 [==============================] - 0s 4ms/step - loss: 0.5307 - accuracy: 0.7659 - val_loss: 0.5756 - val_accuracy: 0.7416\n",
            "Epoch 9/30\n",
            "54/54 [==============================] - 0s 4ms/step - loss: 0.5043 - accuracy: 0.7790 - val_loss: 0.5662 - val_accuracy: 0.7416\n",
            "Epoch 10/30\n",
            "54/54 [==============================] - 0s 4ms/step - loss: 0.5245 - accuracy: 0.7715 - val_loss: 0.5173 - val_accuracy: 0.7472\n",
            "Epoch 11/30\n",
            "54/54 [==============================] - 0s 3ms/step - loss: 0.4636 - accuracy: 0.7697 - val_loss: 0.5729 - val_accuracy: 0.7416\n",
            "Epoch 12/30\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.4982 - accuracy: 0.7921 - val_loss: 0.5200 - val_accuracy: 0.7360\n",
            "Epoch 13/30\n",
            "54/54 [==============================] - 0s 3ms/step - loss: 0.4811 - accuracy: 0.7884 - val_loss: 0.5786 - val_accuracy: 0.7303\n",
            "Epoch 14/30\n",
            "54/54 [==============================] - 0s 3ms/step - loss: 0.4789 - accuracy: 0.7940 - val_loss: 0.5315 - val_accuracy: 0.7360\n",
            "Epoch 15/30\n",
            "54/54 [==============================] - 0s 3ms/step - loss: 0.4591 - accuracy: 0.8034 - val_loss: 0.5313 - val_accuracy: 0.7640\n",
            "Epoch 16/30\n",
            "54/54 [==============================] - 0s 3ms/step - loss: 0.4558 - accuracy: 0.8109 - val_loss: 0.5836 - val_accuracy: 0.7640\n",
            "Epoch 17/30\n",
            "54/54 [==============================] - 0s 3ms/step - loss: 0.4816 - accuracy: 0.7978 - val_loss: 0.5160 - val_accuracy: 0.7416\n",
            "Epoch 18/30\n",
            "54/54 [==============================] - 0s 3ms/step - loss: 0.5003 - accuracy: 0.7959 - val_loss: 0.5551 - val_accuracy: 0.7528\n",
            "Epoch 19/30\n",
            "54/54 [==============================] - 0s 3ms/step - loss: 0.4871 - accuracy: 0.7996 - val_loss: 0.6335 - val_accuracy: 0.7416\n",
            "Epoch 20/30\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.5066 - accuracy: 0.7790 - val_loss: 0.5316 - val_accuracy: 0.7584\n",
            "Epoch 21/30\n",
            "54/54 [==============================] - 0s 3ms/step - loss: 0.4575 - accuracy: 0.8034 - val_loss: 0.5106 - val_accuracy: 0.7528\n",
            "Epoch 22/30\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.4370 - accuracy: 0.8034 - val_loss: 0.5739 - val_accuracy: 0.7360\n",
            "Epoch 23/30\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.5196 - accuracy: 0.7772 - val_loss: 0.5675 - val_accuracy: 0.7753\n",
            "Epoch 24/30\n",
            "54/54 [==============================] - 0s 3ms/step - loss: 0.4421 - accuracy: 0.8109 - val_loss: 0.5154 - val_accuracy: 0.7809\n",
            "Epoch 25/30\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.4504 - accuracy: 0.8127 - val_loss: 0.5366 - val_accuracy: 0.7640\n",
            "Epoch 26/30\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.4649 - accuracy: 0.8071 - val_loss: 0.5752 - val_accuracy: 0.7697\n",
            "Epoch 27/30\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.4625 - accuracy: 0.7996 - val_loss: 0.4921 - val_accuracy: 0.7809\n",
            "Epoch 28/30\n",
            "54/54 [==============================] - 0s 4ms/step - loss: 0.4254 - accuracy: 0.8127 - val_loss: 0.5252 - val_accuracy: 0.7697\n",
            "Epoch 29/30\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.4591 - accuracy: 0.7903 - val_loss: 0.5119 - val_accuracy: 0.7865\n",
            "Epoch 30/30\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.4666 - accuracy: 0.8146 - val_loss: 0.5103 - val_accuracy: 0.7472\n"
          ]
        }
      ],
      "source": [
        "history = model.fit(X_train, Y_train, epochs=30, batch_size=10, validation_data=(X_test, Y_test), verbose=1)"
      ],
      "metadata": {
        "id": "Lb3WDdYgbZmk",
        "outputId": "d80aadb4-b7e5-474d-de3a-ebd302b09860",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1700x1400 with 1 Axes>"
            ],
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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1700x1400 with 1 Axes>"
            ],
            "image/png": 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nPOMZKZfLeclLXpKf/OQn8/FXAQAAAADzSoN2G2q1WsYm1nX6GNs0MjSYQqEwq9cef/zxWbFiRa644oocd9xxOf7445vf22mnnZqPzz333Fx//fV5xStekVe+8pXZbbfdkiTXXnttLr744rz4xS/Of/tv/y1DQ0P58Y9/nEsvvTTf+MY3cvPNN2fx4sXTOsuKFSty1FFH5ZBDDslZZ52V//zP/8yXv/zlnHDCCbnzzjuz++67z+ozAgAAAEA3EtBuw9jEuhz83m90+hjbdMf7XprS8Ox+nI1A9oorrsjxxx+/xYvCbr311vz4xz/Ovvvuu9HXX/SiF+Whhx7KDjvssNHXr7zyypxxxhn567/+67z73e+e1lmuueaafOhDH8q73vWu5tfOP//8fOADH8hll12WP/uzP5v+BwMAAACALmfigGl7xzvesUk4myS77bbbJuFskpx++ulZtGhRvvnNb077PQ444IC84x3v2Ohrb3rTm5IkN9544wxPDAAAAADdTYN2G0aGBnPH+17a6WNs08jQYNvf4/nPf/4Wv/fFL34xf/u3f5ubb745v/zlL7Nu3fpZiAcffHDa73HEEUdkYGDj/91gn332SZI8/vjjMzswAAAAAHQ5Ae02FAqFWU8H9Jot7b9efPHFefvb355dd901J554YvbZZ5+MjIwkST72sY+lWq1O+z0WLVq0ydcWLJj6+98w9AUAAACAXiB5ZNo2dwnZ2rVr8/73vz977rlnbrnllubFYcnUBWt/8Rd/MZ9HBAAAAIDtig1akiSDg1MTCTNtqT766KNZvXp1XvCCF2wUzibJj370o4yNjbXsjAAAAADQawS0JEl23nnnJMnKlStn9LrddtstIyMjufnmm1OpVJpf/+Uvf5lzzz23pWcEAAAAgF5j4oAkyYEHHpi99torn/vc51IsFrPPPvukUChsM2QdGBjIH//xH+fiiy/Oc5/73Lzyla/MmjVr8vWvfz377bdf9tprr3n6BAAAAACw/RHQkmRq4uCLX/xi3vWud+Wzn/1snnjiiSTJaaedts3XXnTRRdl5551z+eWX5xOf+ER23333vP71r8/SpUtz6KGHtvvoAAAAALDdKtRqtVqnD9FOa9asyeLFi7N69eosWrRos8956qmnct999+WAAw7IwoUL5/mEtJqfJwAAAACdNJ1MssEGLQAAAABAhwhoAQAAAAA6REALAAAAANAhAloAAAAAgA4R0AIAAAAAdIiAFgAAAACgQwS0AAAAAAAdIqAFAAAAAOgQAS0AAAAAQIcIaAEAAAAAOkRACwAAAADQIQJaAAAAAIAOEdACAAAAAHTIgk4fgNZ5amJdqmvXZXhwICPDfrQAAAAA0O00aHvI45Xx3P9YJb+sTMz4tcuWLUuhUMjSpUtbf7AtWLp0aQqFQpYtWzZv7wkAAAAA3URA20MGCoUkybrJWodPAgAAAABMh4C2hwwMTAW0kzUBLQAAAABsDwS0PaTRoJ1pgXbp0qU54YQTkiQXXnhhCoVC89eKFSuSJOPj4/noRz+a5z3veSmXy9lxxx3zwhe+MF/5ylc2+fNWr16d9773vTn44IOzww47ZNGiRXnWs56VM844I/fff3+S5Pjjj8+FF16YJDnhhBOa77f//vvP7sMDAAAAwHbITVLbUqslE5VOn2LbhkqpF2hn3KA9/vjjs2LFilxxxRU57rjjcvzxxze/t9NOO6VareZlL3tZli1bliOOOCJvetObMjExka9+9at59atfnY9//OM555xzkiS1Wi0vfelL88Mf/jBHH310Xvayl2VgYCD3339/vvKVr+T000/PfvvtlzPPPDNJcs011+SMM85oBrM77bTTHP8iAAAAAGD7IaDdlolK8r/26vQptu3PH8xAYThJMjnDCm0jkL3iiity/PHHb3JR2Lvf/e4sW7Ys559/frNhmyRPPPFEXvSiF+Vtb3tbXvOa12SvvfbK7bffnh/+8Ic5+eST86UvfWmjP6darWZiYuoCszPPPDMrVqzINddckzPPPHOjUBgAAAAA+oWJgx6yfoO2dX/m5ORkLr300vzqr/7qRuFskuy4445573vfm/Hx8Xzxi1/c6HUjIyOb/FnFYjE77LBD6w4HAAAAANs5DdptGSolf/5gp0+xbUOlDE6sS9LaS8Luuuuu/PKXv8xee+3V3Izd0COPPJIk+elPf5okOeigg3L44Yfns5/9bB544IGcfPLJOf7443PEEUdkYMD/HgAAAAAAGxLQbkuhkAyXO32KaVl/SVjrAtpf/OIXSZLly5dn+fLlW3ze6OhokmTBggX59re/naVLl+af//mf87a3vS1Jsuuuu+acc87Ju9/97gwODrbsfAAAAACwPVNp7CHNiYPJqcu6WmHRokVJklNPPTW1Wm2Lvy677LLma575zGfm4x//eFatWpU77rgjf/3Xf52dd945F1xwQf7iL/6iJecCAAAAgF4goO0h9Xw2tdQy03y20Wpdt27dRl8/6KCDsmjRovzoRz9qXvA1XYVCIQcddFDe+ta35v/+3/+bJPnKV76yzfcEAAAAgH4hoO0hAxtc4DXTmYOdd945SbJy5cqNvr5gwYKcffbZuf/++/P2t799syHt7bffnocffjhJsmLFiqxYsWKT5/z85z9PkixcuHCb7wkAAAAA/cIGbQ8pFAoZKBQyWavNOKA98MADs9dee+Vzn/tcisVi9tlnnxQKhZx77rm58MILc/PNN+ev/uqv8tWvfjXHHntsdtttt6xatSq33XZbfvKTn+QHP/hBdtttt9xyyy15zWtek+c///k5+OCDs8cee2TVqlX5l3/5lwwMDORP/uRPmu95wgknpFAo5M///M+zfPnyLF68ODvttFPOOeecVv/VAAAAAEBXKtRaNVbapdasWZPFixdn9erVzT3Vp3vqqady33335YADDtio4bk9uuPBNVk7OZnn7L5jFg7N7DKuH/7wh3nXu96Vm2++OU888USS5L777sv++++fdevW5VOf+lSuvPLK3HbbbalWq9l9991z8MEH59WvfnVOP/30lMvlPPDAA7nkkkuybNmy3HvvvXn88cezxx575Mgjj8w73vGOHHXUURu95xVXXJGLL744//Ef/5FqtZr99ttvsw3cmeilnycAAAAA25/pZJINAtr0VqD30/9ak/F1k3nWrjukVOzPgnQv/TwBAAAA2P7MJKC1QdtjBuo3hc104gAAAAAAmH8C2h7TuChsUj4LAAAAAF1PQNtj6gVaDVoAAAAA2A4IaHtMo0G7ToUWAAAAALqegLbHrN+g7fBBAAAAAIBtEtD2GBMHAAAAALD9ENBuoNYDoeb6S8K2/88yW73wcwQAAACgPwhokwwODiZJJiYmOnySuWtOHEx2+CAd1Pg5Nn6uAAAAANCtBLRJhoaGUiwWs3r16u2+fTnY5xMHtVotq1evTrFYzNDQUKePAwAAAABbtaDTB+gWu+yyS1atWpUHHnggixcvztDQUAr1uYDtydrx8dTWjme8Opmnnuqf/L1Wq2ViYiKrV6/Ok08+mb333rvTRwIAAACAbRLQ1i1atChJ8uijj2bVqlUdPs3sVcbX5hejE1kzNJDxx4udPs68KxaL2XvvvZs/TwAAAADoZgLaDSxatCiLFi3KxMRE1q1b1+njzMp3/+PhLP3OHTlkr8X5q9cf2OnjzKvBwUGzBgAAAABsVwS0mzE0NLTdBn3FhSNZ9cS6LFqzNgsXLuz0cQAAAACAreifkdI+URoeTDI1dQAAAAAAdDcBbY8pDU+Voker2+dEAwAAAAD0EwFtjykXpxq0Yxq0AAAAAND1BLQ9ptGgrUysy+RkrcOnAQAAAAC2RkDbYxoN2loteWqtmQMAAAAA6GYC2h6zcMFg87EdWgAAAADobgLaHjMwUEhpeCqkrdihBQAAAICuJqDtQc0d2nENWgAAAADoZgLaHtTYodWgBQAAAIDuJqDtQY0GrQ1aAAAAAOhuAtoeZIMWAAAAALYPAtoetD6g1aAFAAAAgG4moO1B5cbEgYAWAAAAALqagLYHlRqXhFVNHAAAAABANxPQ9qDGxIEGLQAAAAB0NwFtD2pMHGjQAgAAAEB3E9D2oFIjoJ3QoAUAAACAbiag7UFlG7QAAAAAsF0Q0PagRoPWBi0AAAAAdDcBbQ9qXBJWGdegBQAAAIBuJqDtQY2AdrSqQQsAAAAA3UxA24PKxamJgzETBwAAAADQ1QS0PajZoDVxAAAAAABdTUDbgxoN2ooGLQAAAAB0NQFtDxoZamzQatACAAAAQDcT0PagRoO2unYy6yZrHT4NAAAAALAlAtoe1NigTZKKHVoAAAAA6FoC2h5UXDCQwYFCEju0AAAAANDNBLQ9qFAopGSHFgAAAAC6noC2R5WKUwGtBi0AAAAAdC8BbY8qD09dFCagBQAAAIDuJaDtUY0G7ahLwgAAAACgawloe1Sp0aCtatACAAAAQLcS0Pao0rAGLQAAAAB0OwFtj2ps0I7ZoAUAAACAriWg7VEatAAAAADQ/QS0PapctEELAAAAAN1OQNujNGgBAAAAoPsJaHtUI6DVoAUAAACA7iWg7VGl+iVhlQkBLQAAAAB0KwFtjyoXGw1aEwcAAAAA0K0EtD2q0aC1QQsAAAAA3UtA26OaG7TjJg4AAAAAoFsJaHtUs0Fr4gAAAAAAupaAtkc1NmjHNGgBAAAAoGsJaHvU+g1aAS0AAAAAdCsBbY9qNGgrLgkDAAAAgK4loO1RpaGpBu3EulrG1052+DQAAAAAwOYIaHvUyPBg87EdWgAAAADoTgLaHjW8YCDDg1M/3lEzBwAAAADQlQS0PaxkhxYAAAAAupqAtoeVh6d2aEerJg4AAAAAoBsJaHtYY4fWxAEAAAAAdCcBbQ8r1wNal4QBAAAAQHcS0PawUmPiQEALAAAAAF1JQNvDyo1LwqomDgAAAACgGwloe9iIBi0AAAAAdDUBbQ9rbNBq0AIAAABAdxLQ9rDGBm1lQoMWAAAAALqRgLaH2aAFAAAAgO4moO1hJRu0AAAAANDVBLQ9rNTYoB3XoAUAAACAbiSg7WHrA1oNWgAAAADoRgLaHlYu1i8JqwpoAQAAAKAbCWh7WKNBO2riAAAAAAC6koC2hzUbtCYOAAAAAKArCWh72MhQvUFb1aAFAAAAgG4koO1hjQbtmAYtAAAAAHQlAW0PK2+wQVur1Tp8GgAAAADg6QS0PaxUb9BO1pLq2skOnwYAAAAAeDoBbQ9rbNAmdmgBAAAAoBsJaHvY4EAhC4emfsQVO7QAAAAA0HUEtD2uPDw1cyCgBQAAAIDuI6DtcaXi+ovCAAAAAIDuIqDtcc0GbVWDFgAAAAC6jYC2x40Ma9ACAAAAQLcS0Pa4RoN2zAYtAAAAAHQdAW2PK2nQAgAAAEDXEtD2uHLRBi0AAAAAdCsBbY/ToAUAAACA7iWg7XGNgLZigxYAAAAAuo6AtseV6peEVTRoAQAAAKDrCGh7XLlYb9DaoAUAAACAriOg7XGNBq0NWgAAAADoPgLaHmeDFgAAAAC6l4C2xzUbtFUNWgAAAADoNgLaHtfcoNWgBQAAAICuI6DtcY0GrYAWAAAAALqPgLbHrW/QmjgAAAAAgG4joO1xpaHGBq0GLQAAAAB0GwFtjyvVG7RjE+syOVnr8GkAAAAAgA0JaHtcub5Bm0yFtAAAAABA99guAtoPf/jDKRQKKRQKuf766zt9nO3KwqGBFApTj0ft0AIAAABAV+n6gPb222/PBRdckHK53OmjbJcKhUKzRVuxQwsAAAAAXaWrA9qJiYmcccYZOeKII3LKKad0+jjbrZHhqR1aDVoAAAAA6C5dHdB+8IMfzPLly/PpT386g4ODnT7OdqtcD2jHxjVoAQAAAKCbLNj2Uzrj5ptvzgc/+MG8733vy8EHH9zp42zXSvWJg1EBLQAAAAB0la4MaKvVat7whjfkiCOOyDvf+c4Zv7ZarTZ/v2bNmlYfb7tTLk41aCtVEwcAAAAA0E26cuLgve99b+6+++5cdtllM542uOiii7J48eLmryVLlrTplNuPEQ1aAAAAAOhKXRfQ/uAHP8hf/uVf5j3veU8OPfTQGb/+vPPOy+rVq5u/Vq5c2YZTbl8aG7QVl4QBAAAAQFfpqomDtWvX5owzzsjhhx+eP/uzP5vVn1EsFlMsFlt8su1bY4O2okELAAAAAF2lqwLaJ598MnfffXeSZHh4eLPPecELXpAk+dKXvpSTTz55vo62XbNBCwAAAADdqasC2mKxmDe96U2b/d61116bu+++O6961auy6667Zv/995/fw23HSjZoAQAAAKArdVVAOzIykk9+8pOb/d6ZZ56Zu+++O+edd16OOuqoeT7Z9q1kgxYAAAAAulLXXRJG660PaDVoAQAAAKCbCGj7QLlYnzioCmgBAAAAoJtsNwHt5ZdfnlqtZt5gFkwcAAAAAEB32m4CWmav7JIwAAAAAOhKAto+0GzQVjVoAQAAAKCbCGj7QKm+QeuSMAAAAADoLgLaPlC2QQsAAAAAXUlA2wcaDVobtAAAAADQXQS0faA0NNWgHV87mbXrJjt8GgAAAACgQUDbB0rFwebjyoQWLQAAAAB0CwFtHxgeHMiCgUKSpFIV0AIAAABAtxDQ9oFCoZBS/aKwUReFAQAAAEDXEND2iXL9ojANWgAAAADoHgLaPjGiQQsAAAAAXUdA2yfKw1MN2rFxDVoAAAAA6BYC2j5hgxYAAAAAuo+Atk/YoAUAAACA7iOg7RMatAAAAADQfQS0faIR0FZs0AIAAABA1xDQ9olS/ZKwigYtAAAAAHQNAW2fKBfrEwc2aAEAAACgawho+4QGLQAAAAB0HwFtn1h/SZgGLQAAAAB0CwFtnyjXG7RjAloAAAAA6BoC2j5Ram7QmjgAAAAAgG4hoO0T5eYGrQYtAAAAAHQLAW2fWL9Bq0ELAAAAAN1CQNsnSo0GbVWDFgAAAAC6hYC2TzQ2aCsatAAAAADQNQS0fWLDDdpardbh0wAAAAAAiYC2bzQatGsnaxlfN9nh0wAAAAAAiYC2b5SGBpuP7dACAAAAQHcQ0PaJBYMDGV4w9eMetUMLAAAAAF1BQNtHysNTLdqxcQ1aAAAAAOgGAto+UqpfFDYqoAUAAACAriCg7SPl+kVhlaqJAwAAAADoBgLaPjKiQQsAAAAAXUVA20caG7QVl4QBAAAAQFcQ0PaRxgZtRYMWAAAAALqCgLaPNDZoR23QAgAAAEBXEND2EQ1aAAAAAOguAto+Uqpv0I7aoAUAAACAriCg7SONS8LGNGgBAAAAoCsIaPtIqTg1cTBaFdACAAAAQDcQ0PaRRoO2YuIAAAAAALqCgLaPNC4JGzVxAAAAAABdQUDbRxqXhFWqGrQAAAAA0A0EtH2ksUFb0aAFAAAAgK4goO0jNmgBAAAAoLsIaPuIDVoAAAAA6C4C2j5igxYAAAAAuouAto+UivWAdmJdarVah08DAAAAAAho+0i5PnFQqyVPTUx2+DQAAAAAgIC2j4wMDTYfj7ooDAAAAAA6TkDbRwYGChvs0LooDAAAAAA6TUDbZxoBrQYtAAAAAHSegLbPlOo7tJVxDVoAAAAA6DQBbZ9pThxo0AIAAABAxwlo+0y5ONWgHbVBCwAAAAAdJ6DtMxq0AAAAANA9BLR9Zv0lYRq0AAAAANBpAto+U65fEjamQQsAAAAAHSeg7TOlYr1Ba4MWAAAAADpOQNtnGg1aG7QAAAAA0HkC2j4zYoMWAAAAALqGgLbPrN+gFdACAAAAQKcJaPvM+g1aEwcAAAAA0GkC2j6zfoNWgxYAAAAAOk1A22dKzQ1aDVoAAAAA6DQBbZ8pNRq0VQ1aAAAAAOg0AW2faWzQViY0aAEAAACg0wS0faasQQsAAAAAXUNA22ds0AIAAABA9xDQ9plycapB+9TEZNZN1jp8GgAAAADobwLaPtNo0CZJRYsWAAAAADpKQNtnigsGMlCYejw2bocWAAAAADpJQNtnCoVC86KwUQEtAAAAAHSUgLYPlYr1i8KqJg4AAAAAoJMEtH2oVG/QVjRoAQAAAKCjBLR9qHFRmEvCAAAAAKCzBLR9qKxBCwAAAABdQUDbh2zQAgAAAEB3END2IQ1aAAAAAOgOAto+NFLfoB21QQsAAAAAHSWg7UPlekA7pkELAAAAAB0loO1DpeLUxMFoVUALAAAAAJ0koO1DjQZtxcQBAAAAAHSUgLYPleqXhI2aOAAAAACAjhLQ9qFSc4NWgxYAAAAAOklA24ds0AIAAABAdxDQ9iEbtAAAAADQHQS0fcgGLQAAAAB0BwFtH2ps0FaqGrQAAAAA0EkC2j5ULtYD2gkNWgAAAADoJAFtH2pMHFRcEgYAAAAAHSWg7UPlekA7vm4y42snO3waAAAAAOhfAto+NFLfoE2SMReFAQAAAEDHCGj70PCCgQwNFpIko+MuCgMAAACAThHQ9qnmDq0GLQAAAAB0jIC2T5XrMwcVDVoAAAAA6BgBbZ8qFacatKNVDVoAAAAA6BQBbZ/SoAUAAACAzhPQ9qmRZkCrQQsAAAAAnSKg7VPl5iVhGrQAAAAA0CkC2j5lgxYAAAAAOk9A26ds0AIAAABA5wlo+1Rjg3bUBi0AAAAAdIyAtk81NmjHBLQAAAAA0DEC2j5VKtYbtFUTBwAAAADQKQLaPtVo0FY0aAEAAACgYwS0farU3KDVoAUAAACAThHQ9qlSo0Fb1aAFAAAAgE4R0PapxgZtZUKDFgAAAAA6RUDbp8oatAAAAADQcQLaPmWDFgAAAAA6T0Dbp8pFDVoAAAAA6DQBbZ9qNGgrE+tSq9U6fBoAAAAA6E8C2j7VCGjXTdZSXTvZ4dMAAAAAQH8S0PapUv2SsCSpjJs5AAAAAIBOEND2qcGBQhYOTf34R6suCgMAAACAThDQ9rFGi1aDFgAAAAA6Q0Dbx5oXhY1r0AIAAABAJwho+1hZgxYAAAAAOkpA28dKxakGrQ1aAAAAAOgMAW0f06AFAAAAgM4S0PaxkfoG7agNWgAAAADoCAFtHyvXA9oxDVoAAAAA6AgBbR8rFacmDkarAloAAAAA6AQBbR9rNGgrJg4AAAAAoCMEtH2sVL8kzAYtAAAAAHSGgLaPlZoNWhMHAAAAANAJAto+1tigrdigBQAAAICOEND2scYGrYkDAAAAAOgMAW0fa2zQmjgAAAAAgM4Q0PaxxgbtaFWDFgAAAAA6QUDbx8rFqYB2bEKDFgAAAAA6QUDbxxoTB6MuCQMAAACAjhDQ9rFyc4PWxAEAAAAAdIKAto+V6hMHlfF1mZysdfg0AAAAANB/BLR9rHFJWGKHFgAAAAA6QUDbxxYuGEyhMPW4Mi6gBQAAAID5JqDtYwMDhZSGGjMHdmgBAAAAYL4JaPtcqTh1UdhoVYMWAAAAAOabgLbPlYc1aAEAAACgUwS0fW5keKpBa4MWAAAAAOafgLbPadACAAAAQOcIaPucDVoAAAAA6BwBbZ/ToAUAAACAzhHQ9rmRekA7aoMWAAAAAOadgLbPlV0SBgAAAAAdI6Dtc6VifeKgauIAAAAAAOabgLbPNRq0Jg4AAAAAYP4JaPtcySVhAAAAANAxAto+V2o0aKsatAAAAAAw3wS0fa5c36Adm9CgBQAAAID5JqDtcxq0AAAAANA5Ato+V7ZBCwAAAAAdI6Dtc6WiBi0AAAAAdIqAts+VhhsbtAJaAAAAAJhvAto+1whoR6smDgAAAABgvglo+1y5fklYde1k1q6b7PBpAAAAAKC/CGj7XKk42HxcMXMAAAAAAPNKQNvnhgcHMjhQSJJUXBQGAAAAAPNKQNvnCoVCc4e2Mm6HFgAAAADmk4CW5g5tZVyDFgAAAADmk4CW5g7taFWDFgAAAADmk4AWDVoAAAAA6BABLRmpb9CO2qAFAAAAgHkloCXl5iVhGrQAAAAAMJ8EtKRUrE8c2KAFAAAAgHkloKXZoB3VoAUAAACAeSWgJaXmJWEatAAAAAAwnwS0pGSDFgAAAAA6QkBLys0NWgEtAAAAAMwnAS3NBu2oiQMAAAAAmFcCWlJubtBq0AIAAADAfBLQkpFGg7aqQQsAAAAA80lAS8rFqYB2bEKDFgAAAADmk4CWlOoTBxq0AAAAADC/BLTYoAUAAACADhHQklLRBi0AAAAAdIKAlpSGbdACAAAAQCcIaGlu0E6sq2V87WSHTwMAAAAA/UNAS7NBmySVcTMHAAAAADBfBLRkaHAgwwum/imMuigMAAAAAOaNgJYk61u0FReFAQAAAMC8EdCSJCnXd2grGrQAAAAAMG8EtCRZ36AdtUELAAAAAPNGQEuSpFSsN2irGrQAAAAAMF8EtCRJyhq0AAAAADDvBLQk2eCSMBu0AAAAADBvBLQkSUouCQMAAACAeSegJUlSLtYbtFUTBwAAAAAwXwS0JFnfoB3VoAUAAACAeSOgJcn6S8IqLgkDAAAAgHkjoCVJMmKDFgAAAADmnYCWJBts0GrQAgAAAMC8EdCSZIMN2qoGLQAAAADMFwEtSWzQAgAAAEAnCGhJkozUA1oNWgAAAACYPwJakiTl4tTEwdiEgBYAAAAA5ouAliRJqdmgNXEAAAAAAPNFQEuSpFy/JKwyrkELAAAAAPNFQEuSpFSsN2jH16ZWq3X4NAAAAADQHwS0JElK9QZtrZY8NTHZ4dMAAAAAQH8Q0JIkGRkabD6ujNuhBQAAAID5IKAlSTI4UGiGtHZoAQAAAGB+CGhpKm+wQwsAAAAAtJ+AlqbGDu1oVYMWAAAAAOaDgJam0vBUg3bMxAEAAAAAzAsBLU2NgNbEAQAAAADMDwEtTeXi1MRBRUALAAAAAPNCQEtTs0FrgxYAAAAA5oWAlqbGJWEatAAAAAAwPwS0NDUatBWXhAEAAADAvBDQ0rR+g1ZACwAAAADzQUBL0/oNWhMHAAAAADAfBLQ0lYc1aAEAAABgPgloaRrRoAUAAACAeSWgpalcnApoxyY0aAEAAABgPghoaSrVJw40aAEAAABgfghoabJBCwAAAADzS0BLU6k+cTA6rkELAAAAAPNBQEtTqX5J2JgGLQAAAADMCwEtTeXmBq2AFgAAAADmg4CWpmaDdmJd1k3WOnwaAAAAAOh9AlqaysUFzcdjE1q0AAAAANBuXRfQPvXUU/nTP/3THHvssdlrr72ycOHC7LHHHjn66KNz2WWXZWJiotNH7FnFBQMpFKYeV6ouCgMAAACAduu6gPbJJ5/MpZdemkKhkFe84hX50z/905xyyilZtWpVzjrrrJx00kmZnJzs9DF7UqFQaO7QVlwUBgAAAABtt2DbT5lfO++8c1avXp3h4eGNvr527dr89m//dv793/89X//61/OKV7yiQyfsbaXhwTxZXZvRcQ1aAAAAAGi3rmvQDgwMbBLOJsmCBQtyyimnJEnuueee+T5W32js0GrQAgAAAED7dV1AuyWTk5P5t3/7tyTJoYce2uHT9K7S8GCSZNQGLQAAAAC0XddNHDSMj4/nf/2v/5VarZbHHnss3/rWt/LTn/40b3zjG/PiF794i6+rVqupVqvN369Zs2Y+jtszGgGtBi0AAAAAtF9XB7QXXnhh8/eFQiFvf/vbc9FFF231dRdddNFGr2NmSi4JAwAAAIB507UTBzvssENqtVrWrVuXlStX5pJLLsknP/nJHH/88VttxZ533nlZvXp189fKlSvn8dTbv3Kx0aA1cQAAAAAA7da1AW3DwMBA9tlnn5x99tn5u7/7u1x33XX54Ac/uMXnF4vFLFq0aKNfTF+jQTta1aAFAAAAgHbr+oB2QyeeeGKSZNmyZZ09SA8rD2vQAgAAAMB82a4C2gcffDBJMjQ01OGT9K4RG7QAAAAAMG+6LqC94447UqlUNvl6pVLJn/7pnyZJfud3fme+j9U3NGgBAAAAYP4s6PQBnu4LX/hCPvrRj+aYY47J/vvvn0WLFmXVqlX5+te/nsceeywvfOEL8yd/8iedPmbPKhVt0AIAAADAfOm6gPakk07Kgw8+mO9///v5wQ9+kCeffDKLFy/O4Ycfnte97nU566yzsmBB1x27Z2jQAgAAAMD86bqk88gjj8yRRx7Z6WP0rZF6QKtBCwAAAADt13UbtHRWuXFJ2ISAFgAAAADaTUDLRkrF+sRB1cQBAAAAALSbgJaNNBu04xq0AAAAANBuAlo2Uq43aEddEgYAAAAAbSegZSMjjQatS8IAAAAAoO0EtGykPDzVoB1fN5mJdZMdPg0AAAAA9DYBLRsp1Ru0iR1aAAAAAGg3AS0bGV4wkKHBQpKkYocWAAAAANpKQMsmGi3aUTu0AAAAANBWAlo2Uarv0I6ZOAAAAACAthLQsolGQDtq4gAAAAAA2kpAyybKxamJAxu0AAAAANBeAlo20WzQ2qAFAAAAgLYS0LKJxiVhGrQAAAAA0F4CWjbRaNBWXBIGAAAAAG0loGUT5WaDVkALAAAAAO0koGUTpWJjg9bEAQAAAAC0k4CWTWjQAgAAAMD8ENCyiZHmBq0GLQAAAAC0k4CWTZTrAe2oBi0AAAAAtJWAlk2UivWJAxu0AAAAANBWAlo20dig1aAFAAAAgPYS0LKJUtEGLQAAAADMBwEtmygNNQJaDVoAAAAAaCcBLZsoNzdoBbQAAAAA0E4CWjZRGp5q0I6aOAAAAACAthLQsolmg3Z8XWq1WodPAwAAAAC9S0DLJkbqDdp1k7VU1052+DQAAAAA0LsEtGyicUlYkoy5KAwAAAAA2kZAyyYWDA6kuGDqn4YdWgAAAABoHwEtm7XhDi0AAAAA0B4CWjarVN+hHa1q0AIAAABAuwho2axGQGuDFgAAAADaR0DLZpWGpyYORgW0AAAAANA2Alo2q1ycatBWXBIGAAAAAG0joGWzmg3aqgYtAAAAALSLgJbNKg9r0AIAAABAuwlo2ayReoO2YoMWAAAAANpGQMtmNRq0oxq0AAAAANA2Alo2q1SsN2ht0AIAAABA2who2SwNWgAAAABoPwEtm1VqXBKmQQsAAAAAbSOgZbNKjUvCJgS0AAAAANAuAlo2q1xsNGhNHAAAAABAuwho2axGg3Z0XIMWAAAAANpFQMtmNRu0LgkDAAAAgLYR0LJZI0P1DVoNWgAAAABoGwEtm2WDFgAAAADaT0DLZjU2aCsT6zI5WevwaQAAAACgNwlo2axGg7ZWS55aa+YAAAAAANpBQMtmLVwwmEJh6vFoVUALAAAAAO0goGWzBgYKGRmaatGOuSgMAAAAANpCQMsWNXZoR8ddFAYAAAAA7SCgZYsaO7QVAS0AAAAAtIWAli1qNmht0AIAAABAWwho2aLSsAYtAAAAALSTgJYtWh/QatACAAAAQDsIaNmicvOSMAEtAAAAALSDgJYtKjUuCauaOAAAAACAdhDQskUatAAAAADQXgJatqixQTvmkjAAAAAAaAsBLVtU0qAFAAAAgLYS0LJFZRu0AAAAANBWAlq2SIMWAAAAANpLQMsWNRu0NmgBAAAAoC0EtGzRyFAjoNWgBQAAAIB2ENCyReXi1MRBpSqgBQAAAIB2ENCyRaXhqQbtqIkDAAAAAGgLAS1b1GzQmjgAAAAAgLYQ0LJFjQ3a0aoGLQAAAAC0g4CWLWo0aKtrJ7Nustbh0wAAAABA7xHQskWNDdokqdihBQAAAICWE9CyRcUFAxkcKCSxQwsAAAAA7SCgZYsKhUKzRWuHFgAAAABaT0DLVjUCWg1aAAAAAGg9AS1bVR6euihMQAsAAAAArSegZatKxfrEgUvCAAAAAKDlBLRsVanRoK1q0AIAAABAqwlo2arysAYtAAAAALSLgJatajRox2zQAgAAAEDLCWjZqpIGLQAAAAC0jYCWrSoXbdACAAAAQLsIaNkqDVoAAAAAaB8BLVvVCGg1aAEAAACg9QS0bFXjkrDKhIAWAAAAAFpNQMtWlYuNBq2JAwAAAABoNQEtW9Vo0NqgBQAAAIDWE9CyVc0G7biJAwAAAABoNQEtWzUyVN+gFdACAAAAQMsJaNkqG7QAAAAA0D4CWrZq/QatBi0AAAAAtJqAlq1av0GrQQsAAAAArSagZasaDdqJdbWMr53s8GkAAAAAoLcIaNmq0vBg8/GYmQMAAAAAaCkBLVs1NDiQ4cGpfyajZg4AAAAAoKUEtGxTyQ4tAAAAALSFgJZtKtd3aEerJg4AAAAAoJUEtGzTyHCjQSugBQAAAIBWEtCyTeVhEwcAAAAA0A4CWrap1Jg40KAFAAAAgJYS0LJN5cYlYVUNWgAAAABoJQEt26RBCwAAAADtMaeAduXKlfn2t7+dSqXS/Nrk5GQ+/OEP5+ijj85LXvKSfPWrX53zIemsUn2DdswGLQAAAAC01IK5vPj888/P1VdfnYceeqj5tQ9+8IO54IILmr+/5ppr8v3vfz+/+Zu/OZe3ooM0aAEAAACgPebUoL3uuuvykpe8JENDQ0mSWq2Wv/7rv86BBx6Yn/3sZ7nhhhtSLpfzkY98pCWHpTNs0AIAAABAe8wpoH344Yez3377NX9/yy235JFHHsm5556bffbZJ0ceeWROPvnk3HjjjXM+KJ2jQQsAAAAA7TGngHZycjKTk5PN3y9btiyFQiEvetGLml/be++9N5pAYPvTbNDaoAUAAACAlppTQLvvvvvmhhtuaP7+X/7lX7Lnnnvm137t15pfe+ihh7LTTjvN5W3osJGhRkCrQQsAAAAArTSngPbUU0/Nddddl//+3/97TjvttHzve9/LqaeeutFz7rjjjvzKr/zKnA5JZ5WLUxMHlaqAFgAAAABaacFcXvz2t789//7v/54vfvGLSZLDDz88S5cubX7//vvvzw033JA/+7M/m9Mh6azS8FSDdtTEAQAAAAC01JwC2kWLFuX666/P7bffniQ56KCDMjg4uNFzvvjFL+bII4+cy9vQYc0GrYkDAAAAAGipOQW0DYceeuhmv77ffvtlv/32a8Vb0EHrN2g1aAEAAACglea0QfvEE0/k3nvvzcTExEZf//znP5/f//3fzx/8wR/kxz/+8ZwOSOfZoAUAAACA9phTg/ad73xnrrrqqvz85z/P0NBQkuTSSy/NOeeck1qtliT57Gc/m5tuuikHHnjg3E9LR5Q32KCt1WopFAodPhEAAAAA9IY5NWivueaavOQlL0mpVGp+7UMf+lD23nvvXHvttfnCF76QWq2Wj3zkI3M+KJ1TqjdoJ2tJde1kh08DAAAAAL1jTg3a//qv/8rLXvay5u/vvPPOrFy5Mn/xF3+RY445JknyT//0T7n22mvndko6qrFBmySj1bVZODS4lWcDAAAAANM1pwZttVrN8PBw8/fXXHNNCoVCTjzxxObXfuVXfiWrVq2ay9vQYYMDhSwcmvqnUhm3QwsAAAAArTKngHafffbJrbfe2vz9v/7rv2bnnXfO4Ycf3vzaY489lh122GEub0MXKA/XLwoT0AIAAABAy8xp4uDlL395Lrnkkrz97W/PwoUL82//9m95wxvesNFz/uM//iP77rvvnA5J55WKg3lsdOqiMAAAAACgNeYU0J533nm5+uqr89GPfjRJsueee+Z973tf8/sPP/xwrrvuupxzzjlzOyUd12zQVjVoAQAAAKBV5hTQ7rHHHlm+fHm+9a1vJUmOPfbYLFq0qPn9Rx99NB/5yEfy0pe+dG6npONKw1MXg2nQAgAAAEDrzCmgTZKRkZGcdNJJm/3ewQcfnIMPPniub0EXKNUbtGM2aAEAAACgZeYc0DasWrUqt9xyS9asWZNFixbliCOOyN57792qP54O06AFAAAAgNabc0B7zz335Oyzz863v/3tTb734he/OJ/4xCfyrGc9a65vQ4eVizZoAQAAAKDV5hTQrly5Msccc0wefvjhHHjggTn22GOz55575qGHHsq1116bb37zm3nhC1+YG264IUuWLGnVmekADVoAAAAAaL05BbQXXnhhHn744XziE5/Im9/85hQKhY2+/7d/+7c5++yz8773vS9///d/P6eD0lmNgNYGLQAAAAC0zpwC2m984xt55Stfmbe85S2b/f6b3/zmfO1rX8vXv/71ubwNXaBxSZgGLQAAAAC0zsBcXvzwww/n0EMP3epzDj300DzyyCNzeRu6QLk41aC1QQsAAAAArTOngHbXXXfNHXfcsdXn3HHHHdl1113n8jZ0AQ1aAAAAAGi9OQW0L33pS/OVr3wln/rUpzb7/U9/+tO5+uqr87KXvWwub0MXaDZobdACAAAAQMvMaYP2ggsuyNVXX50/+qM/ysc+9rEcd9xx2X333fPzn/881157bZYvX55ddtklF1xwQavOS4eMDE39UxHQAgAAAEDrzCmg3XfffXPdddflzW9+c5YtW5bly5dv9P0TTjghl156aZYsWTKnQ9J5jQbtaNXEAQAAAAC0ypwC2iR59rOfnW9/+9tZuXJlbrnllqxZsyaLFi3KEUccIZjtIY0NWg1aAAAAAGidOQe0DUuWLBHI9rD1G7QatAAAAADQKjMKaM8666xZvUmhUNjiRWJsH8r1Bu1oVYMWAAAAAFplRgHt5ZdfPqs3EdBu/0aGpxq0YxPrMjlZy8BAocMnAgAAAIDt34wC2vvuu69d56DLNRq0yVRIWy62bB0DAAAAAPrWjFK2/fbbr13noMstHBpIoZDUasno+FoBLQAAAAC0wECnD8D2oVAoNFu0FTu0AAAAANASAlqmrbFDWxkX0AIAAABAKwhombZyM6Bd2+GTAAAAAEBvENAybaX6xMGoBi0AAAAAtISAlmkrF+sN2qoGLQAAAAC0goCWadOgBQAAAIDWEtAybaX6Bu2YDVoAAAAAaAkBLdOmQQsAAAAArSWgZdps0AIAAABAawlomTYNWgAAAABoLQEt01aub9BWbNACAAAAQEsIaJm2kWZAq0ELAAAAAK0goGXaysX6xEFVQAsAAAAArSCgZdpKJg4AAAAAoKUEtExb2SVhAAAAANBSAlqmrdGgHdOgBQAAAICWENAybSUbtAAAAADQUgJapq1sgxYAAAAAWkpAy7Q1G7Q2aAEAAACgJQS0TFujQTu+djJr1012+DQAAAAAsP0T0DJtI/WANkkqE1q0AAAAADBXAlqmbXhwIAsGCkmSiovCAAAAAGDOBLRMW6FQSKneoh11URgAAAAAzJmAlhkp1y8K06AFAAAAgLkT0DIjGrQAAAAA0DoCWmakNDzVoB0b16AFAAAAgLkS0DIjGrQAAAAA0DoCWmbEBi0AAAAAtI6AlhnRoAUAAACA1hHQMiONgLZigxYAAAAA5kxAy4w0LgmraNACAAAAwJwJaJmRcrE+cWCDFgAAAADmTEDLjGjQAgAAAEDrCGiZkXLzkjANWgAAAACYKwEtM9Jo0I4JaAEAAABgzgS0zEipuUFr4gAAAAAA5kpAy4yUmxu0GrQAAAAAMFcCWmak1Nyg1aAFAAAAgLkS0DIj5WK9QVvVoAUAAACAuRLQMiMj9QZtRYMWAAAAAOZMQMuMbLhBW6vVOnwaAAAAANi+CWiZkVJxqkG7drKW8XWTHT4NAAAAAGzfBLTMSGlosPnYDi0AAAAAzI2AlhlZMDiQ4QVT/2wqEwJaAAAAAJgLAS0zVm5cFFZ1URgAAAAAzIWAlhkr1S8KGx3XoAUAAACAuRDQMmPlogYtAAAAALSCgJYZ06AFAAAAgNYQ0DJjpcYG7bgGLQAAAADMhYCWGWs0aCsatAAAAAAwJwJaZqyxQTtqgxYAAAAA5kRAy4xp0AIAAABAawhombFyc4NWQAsAAAAAcyGgZcZcEgYAAAAArSGgZcZKxamJg9GqBi0AAAAAzIWAlhkra9ACAAAAQEsIaJmxxiVhozZoAQAAAGBOBLTMWGODdkyDFgAAAADmREDLjNmgBQAAAIDWENAyYzZoAQAAAKA1BLTMmA1aAAAAAGgNAS0zVi7WG7RVDVoAAAAAmAsBLTM20pg4mFiXWq3W4dMAAAAAwPZLQMuMlesTB7Va8tTEZIdPAwAAAADbLwEtMzYyNNh8POqiMAAAAACYNQEtMzYwUEipMXNQdVEYAAAAAMyWgJZZKdVnDioTGrQAAAAAMFsCWmal0aAd1aAFAAAAgFkT0DIrzYkDG7QAAAAAMGsCWmalXJyaONCgBQAAAIDZE9AyKxq0AAAAADB3AlpmZX1Aq0ELAAAAALMloGVWysNTEwcatAAAAAAwewJaZqVUnGrQ2qAFAAAAgNkT0DIrGrQAAAAAMHcCWmalVA9oR23QAgAAAMCsCWiZlcYlYWMCWgAAAACYNQEts7J+g9bEAQAAAADMloCWWVm/QatBCwAAAACzJaBlVhoTB6MuCQMAAACAWRPQMivl4lSD1gYtAAAAAMyegJZZGdGgBQAAAIA5E9AyK80N2qoGLQAAAADMloCWWbFBCwAAAABzJ6BlVhobtE9NTGbdZK3DpwEAAACA7ZOAlllpNGiTZGzCzAEAAAAAzEbXBbSrVq3Kxz72sZx44onZd999Mzw8nD322COnnnpqfvjDH3b6eNQVFwxkoDD1uFI1cwAAAAAAs9F1Ae3HP/7x/Mmf/EnuvffenHjiiXnb296WY445Jl/+8pfzW7/1W/n85z/f6SOSpFAoNC8KGx3XoAUAAACA2VjQ6QM83fOf//wsW7Ysxx133EZf/+53v5sXv/jFOfvss3PyySenWCx26IQ0lIqDeaK6NqMatAAAAAAwK13XoH3Na16zSTibJC984Qtzwgkn5Je//GVuu+22DpyMp2s0aCsatAAAAAAwK10X0G7N0NBQkmTBgq4r/valkfpFYZVxDVoAAAAAmI3tJun82c9+lm9+85vZc889c9hhh23xedVqNdVqtfn7NWvWzMfx+pIGLQAAAADMzXbRoJ2YmMjpp5+earWaD3/4wxkcHNzicy+66KIsXry4+WvJkiXzeNL+UipO/Rxs0AIAAADA7HR9QDs5OZkzzzwz1157bf7wD/8wp59++laff95552X16tXNXytXrpynk/YfDVoAAAAAmJuunjiYnJzMWWedlX/4h3/Iaaedlr/5m7/Z5muKxWKKxeI8nI5Sc4NWQAsAAAAAs9G1Ae3k5GTe+MY35sorr8zrX//6XH755RkY6PrCb18puSQMAAAAAOakKxPPDcPZ3/u938tnPvOZre7O0hml4lS+P1rVoAUAAACA2ei6gLYxa3DllVfmta99ba666irhbJcqa9ACAAAAwJx03cTB+973vlxxxRXZYYcd8pznPCcf+MAHNnnOySefnCOOOGL+D8dGSvVLwkZt0AIAAADArHRdQLtixYokyZNPPpkPfvCDm33O/vvvL6DtAo0N2jENWgAAAACYla4LaC+//PJcfvnlnT4G02CDFgAAAADmpus2aNl+2KAFAAAAgLkR0DJrNmgBAAAAYG4EtMxauVhv0FY1aAEAAABgNgS0zFrjkrDKhAYtAAAAAMyGgJZZa0wcVFwSBgAAAACzIqBl1sr1gHZ83WTG1052+DQAAAAAsP0R0DJrI/WJgyQZc1EYAAAAAMyYgJZZG14wkOHBqX9ClQkXhQEAAADATAlomZNGi3bUDi0AAAAAzJiAljkp1wPayrgGLQAAAADMlICWOSkVpy4K06AFAAAAgJkT0DInGrQAAAAAMHsCWuZkpBnQatACAAAAwEwJaJmT8vDUxIEGLQAAAADMnICWObFBCwAAAACzJ6BlTmzQAgAAAMDsCWiZk1J94mDUBi0AAAAAzJiAljkp1Ru0YwJaAAAAAJgxAS1zUipOBbSjVRMHAAAAADBTAlrmpFyfOKho0AIAAADAjAlomZPGxMGoS8IAAAAAYMYEtMxJuahBCwAAAACzJaBlTkbqDdqKBi0AAAAAzJiAljlpbtBWNWgBAAAAYKYEtMyJDVoAAAAAmD0BLXPS3KDVoAUAAACAGRPQMieNBm1lYl1qtVqHTwMAAAAA2xcBLXPSCGjXTdZSXTvZ4dMAAAAAwPZFQMuclOqXhCVJZdzMAQAAAADMhICWORkcKGTh0NQ/o9Gqi8IAAAAAYCYEtMxZud6iHZvQoAUAAACAmRDQMmcj9R1aDVoAAAAAmBkBLXPWaNDaoAUAAACAmRHQMmelogYtAAAAAMyGgJY506AFAAAAgNkR0DJnpfoGrYAWAAAAAGZGQMucrQ9oTRwAAAAAwEwIaJmzUnFq4mC0qkELAAAAADMhoGXOyhq0AAAAADArAlrmrFS/JGxUQAsAAAAAMyKgZc5cEgYAAAAAsyOgZc4aG7QVG7QAAAAAMCMCWuassUFr4gAAAAAAZkZAy5w1NmhNHAAAAADAzAhombNy0QYtAAAAAMyGgJY5W39JmIkDAAAAAJgJAS1z1pg4GHVJGAAAAADMiICWOSs3N2g1aAEAAABgJgS0zFlpgw3ayclah08DAAAAANsPAS1z1mjQJslTa80cAAAAAMB0CWiZs4VDAykUph7boQUAAACA6RPQMmeFQiGlocbMgR1aAAAAAJguAS0tUSpOzRxo0AIAAADA9AloaYnysAYtAAAAAMyUgJaWGKlfFFYZ16AFAAAAgOkS0NISGrQAAAAAMHMCWlrCBi0AAAAAzJyAlpbQoAUAAACAmRPQ0hIlG7QAAAAAMGMCWlqiVG/QjgpoAQAAAGDaBLS0RKlYnziomjgAAAAAgOkS0NIS5frEgQYtAAAAAEyfgJaWKLkkDAAAAABmTEBLS5SLLgkDAAAAgJkS0NISGrQAAAAAMHMCWlqi1NigrWrQAgAAAMB0CWhpibIGLQAAAADMmICWligVNWgBAAAAYKYEtLREY4N2bEJACwAAAADTJaClJRoB7WjVxAEAAAAATJeAlpYo1y8Jq66dzNp1kx0+DQAAAABsHwS0tESpONh8XDFzAAAAAADTIqClJYYHB7JgoJAkGRsX0AIAAADAdAhoaYlCoZARO7QAAAAAMCMCWlqmsUNb0aAFAAAAgGkR0NIyjR1aDVoAAAAAmB4BLS2jQQsAAAAAMyOgpWVK9Q1aAS0AAAAATI+AlpZpBLSj4yYOAAAAAGA6BLS0TKlYnziwQQsAAAAA0yKgpWXKzQatiQMAAAAAmA4BLS1Tal4SpkELAAAAANMhoKVlXBIGAAAAADMjoKVlys0NWgEtAAAAAEyHgJaWKTU3aE0cAAAAAMB0CGhpmXJzg1aDFgAAAACmQ0BLy5SKjQ1aDVoAAAAAmA4BLS3jkjAAAAAAmBkBLS1Tqk8cjFY1aAEAAABgOgS0tIwNWgAAAACYGQEtLdPYoNWgBQAAAIDpEdDSMo0G7diEBi0AAAAATIeAlpYZqV8SNrGulvG1kx0+DQAAAAB0PwEtLVOqB7RJUhk3cwAAAAAA2yKgpWWGBgcyvGDqn9Soi8IAAAAAYJsEtLRUud6irbgoDAAAAAC2SUBLS5XqF4VVNGgBAAAAYJsEtLRUY4d21AYtAAAAAGyTgJaWKhXrDdqqBi0AAAAAbIuAlpYqa9ACAAAAwLQJaGmpxgbtmA1aAAAAANgmAS0ttX6DVkALAAAAANsioKWlysWpgLZSNXEAAAAAANsioKWlGhMHGrQAAAAAsG0CWlqqcUlYxSVhAAAAALBNAlpaqlScatBWNGgBAAAAYJsEtLRUSYMWAAAAAKZNQEtLNTdoqxq0AAAAALAtAlpaygYtAAAAAEyfgJaWskELAAAAANMnoKWl1m/QCmgBAAAAYFsEtLRUI6AdrZo4AAAAAIBtEdDSUuVhEwcAAAAAMF0CWlqqVKw3aMfXplardfg0AAAAANDdBLS0VKNBW6sl1bWTHT4NAAAAAHQ3AS0tNTI02HxshxYAAAAAtk5AS0sNDBSaIa0dWgAAAADYOgEtLVfeYIcWAAAAANgyAS0tV6rv0I5WNWgBAAAAYGsEtLRcaXiqQTtm4gAAAAAAtkpAS8s1AloTBwAAAACwdQJaWq5cnJo4qAhoAQAAAGCrBLS0XLNBa4MWAAAAALZKQEvLleuXhNmgBQAAAICtE9DSciM2aAEAAABgWgS0tNz6DVoNWgAAAADYGgEtLbd+g1aDFgAAAAC2RkBLyzU2aDVoAQAAAGDrBLS0XKk41aCt2KAFAAAAgK0S0NJyjYkDDVoAAAAA2DoBLS1Xqk8c2KAFAAAAgK0T0NJyNmgBAAAAYHoEtLRcY4N21AYtAAAAAGyVgJaWazRoxzRoAQAAAGCrBLS0XOOSsNGqgBYAAAAAtkZAS8s1AtqxiXVZN1nr8GkAAAAAoHsJaGm5cnFB8/HYhBYtAAAAAGyJgJaWKy4YyEBh6nHFRWEAAAAAsEUCWlquUCikVL8orGKHFgAAAAC2SEBLWzQvCtOgBQAAAIAtEtDSFo0d2sq4Bi0AAAAAbImAlrZoNmirGrQAAAAAsCUCWtqiXN+gHdOgBQAAAIAtEtDSFiPNDVoBLQAAAABsiYCWtigXpwLaikvCAAAAAGCLBLS0Rak+cTBa1aAFAAAAgC0R0NIW5WENWgAAAADYFgEtbVEqTjVoKzZoAQAAAGCLBLS0RWlIgxYAAAAAtkVAS1s0GrQ2aAEAAABgywS0tIUNWgAAAADYNgEtbWGDFgAAAAC2TUBLWzQ2aEcFtAAAAACwRQJa2qJUrE8cVE0cAAAAAMCWCGhpi/KwiQMAAAAA2BYBLW1RLjYmDjRoAQAAAGBLBLS0RUmDFgAAAAC2SUBLW5SGpxq042snM7FussOnAQAAAIDuJKClLRoN2kSLFgAAAAC2REBLWwwvGMjQYCFJUrFDCwAAAACbJaClbRot2tGqBi0AAAAAbI6AlrYp13dox0wcAAAAAMBmCWhpm5F6QDtq4gAAAAAANktAS9uUi1MTBzZoAQAAAGDzBLS0TanRoLVBCwAAAACbJaClbcr1S8Js0AIAAADA5gloaRsbtAAAAACwdQJa2qbRoK1o0AIAAADAZgloaZtSsbFBq0ELAAAAAJsjoKVtNGgBAAAAYOsEtLRNo0FbsUELAAAAAJsloKVtSkONS8I0aAEAAABgcwS0tE2pWJ84sEELAAAAAJsloKVtGhu0GrQAAAAAsHkCWtrGBi0AAAAAbJ2AlrZpNGgrGrQAAAAAsFkCWtqmNFxv0FYFtAAAAACwOQJa2qYR0I6aOAAAAACAzRLQ0jbl4vqJg1qt1uHTAAAAAED3EdDSNo0G7brJWsbXTXb4NAAAAADQfQS0tE2pfklYYocWAAAAADZHQEvbDA4UUlww9U/MDi0AAAAAbEpAS1ttuEMLAAAAAGxMQEtbNXZoR6satAAAAADwdAJa2qpc36Ed06AFAAAAgE0IaGmrkUaDVkALAAAAAJsQ0NJW5eJUQFtxSRgAAAAAbEJAS1uV6hMHo1UNWgAAAAB4OgEtbVUe1qAFAAAAgC0R0NJWpeJUg7ZigxYAAAAANiGgpa1KQ41LwjRoAQAAAODpBLS0VbNBa4MWAAAAADYhoKWtGhu0GrQAAAAAsCkBLW3VaNCO2aAFAAAAgE0IaGmr9Ru0AloAAAAAeDoBLW1VLk4FtJWqiQMAAAAAeDoBLW1VGp6aONCgBQAAAIBNCWhpq2aD1iVhAAAAALAJAS1t1WjQVjRoAQAAAGATAlraqjRsgxYAAAAAtkRAS1s1G7QT6zI5WevwaQAAAACguwhoaavGBm2tljy11swBAAAAAGxIQEtbLVwwmEJh6rEdWgAAAADYmICWthoYKKQ01NihFdACAAAAwIYEtLTdSH2HdnTcRWEAAAAAsCEBLW3X2KGtCGgBAAAAYCMCWtqu1GjQmjgAAAAAgI0IaGm78nCjQSugBQAAAIANCWhpu5FhEwcAAAAAsDkCWtqu3LwkTIMWAAAAADYkoKXtSo1LwqoatAAAAACwIQEtbadBCwAAAACbJ6Cl7RoN2jEbtAAAAACwEQEtbVca0qAFAAAAgM0R0NJ2ZRu0AAAAALBZAlrarmSDFgAAAAA2S0BL25WbG7QCWgAAAADYkICWtlvfoDVxAAAAAAAbEtDSdqXhxgatBi0AAAAAbEhAS9s1AloNWgAAAADYmICWtisXpyYOKjZoAQAAAGAjAlrarjlxoEELAAAAABsR0NJ2jUvCnpqYzLrJWodPAwAAAADdQ0BL2zUatIkWLQAAAABsqCsD2quuuipvfvObc+SRR6ZYLKZQKOTyyy/v9LGYpeKCgQwOFJLYoQUAAACADS3o9AE25z3veU/uv//+7LLLLtlzzz1z//33d/pIzEGhUEhpeDBPPLU2o1UNWgAAAABo6MoG7Sc/+cmsWLEijzzySN7ylrd0+ji0QLm+Q6tBCwAAAADrdWWD9iUveUmnj0CLNXZoBbQAAAAAsF5XNmjpPaXiVEA76pIwAAAAAGjqygbtXFSr1VSr1ebv16xZ08HT0FBqTBxUNWgBAAAAoKHnGrQXXXRRFi9e3Py1ZMmSTh+JJOXmxIEGLQAAAAA09FxAe95552X16tXNXytXruz0kUhSKrokDAAAAACerucmDorFYorFYqePwdOUhmzQAgAAAMDT9VyDlu5ULtqgBQAAAICnE9AyL0rDGrQAAAAA8HQCWuZFo0E7ZoMWAAAAAJq6coP2k5/8ZL73ve8lSW677bbm15YtW5YkOeaYY/IHf/AHnToeszDS3KAV0AIAAABAQ1cGtN/73vdyxRVXbPS16667Ltddd13z9wLa7Uu5OBXQVqomDgAAAACgoSsD2ssvvzyXX355p49BC5WGp/6p2aAFAAAAgPVs0DIvmg1aEwcAAAAA0CSgZV40GrQCWgAAAABYT0DLvCgN26AFAAAAgKcT0DIv1m/QatACAAAAQIOAlnmxfoNWgxYAAAAAGgS0zItGg3ZiXS3jayc7fBoAAAAA6A4CWuZFY4M2ScbMHAAAAABAEgEt82RocCDDg1P/3EbNHAAAAABAEgEt86hkhxYAAAAANiKgZd6U6zu0o1UTBwAAAACQCGiZR40d2ooNWgAAAABIIqBlHq0PaE0cAAAAAEAioGUelRoTBxq0AAAAAJBEQMs8KjcuCatq0AIAAABAIqBlHmnQAgAAAMDGBLTMm0aDdswGLQAAAAAkEdAyj0aGNGgBAAAAYEMCWuaNDVoAAAAA2JiAlnljgxYAAAAANiagZd6s36AV0AIAAABAIqBlHq1v0Jo4AAAAAIBEQMs8Kg03Nmg1aAEAAAAgEdAyjxoBrQYtAAAAAEwR0DJvysWpiYOKDVoAAAAASCKgZR41Jw40aAEAAAAgiYCWedS4JMwGLQAAAABMEdD2mrHHO32CLSpvsEFbq9U6fBoAAAAA6DwBbS/5z+8kHzs8+elXO32SzSrVN2gna0l17WSHTwMAAAAAnSeg7SXLv5RUVyf/eGZy7zWdPs0mRoYGm49Hq3ZoAQAAAEBA20te8dHkwJOSdePJZ1+fPPCjTp9oI4MDhWZIWxm3QwsAAAAAAtpeMrggOfVTyQHHJROjyVWnJj+/o9On2khpWEALAAAAAA0C2l4ztDB53T8kex+ZPPV48plTkl/c1+lTNZWK6y8KAwAAAIB+J6DtRcUdkt//x2S3g5MnH0qufHWy5r86faokSXl46qKwSlWDFgAAAAAEtL2qtHNy+peSZ+yfPH5/8pmTk8ovOn2qDSYONGgBAAAAQEDby3bcI3nDl5Md90we+enUJm31iY4eqVysN2ht0AIAAACAgLbnPWP/5PR/SUZ2Th68Ofns65OJpzp2nJEhG7QAAAAA0CCg7Qe7HZic9k/J8A7Jiu8m//TGZN1ER47SbNDaoAUAAAAAAW3f2Ps3ktd/LhksJnd9LfnyW5PJyXk/RmODVoMWAAAAAAS0/eWAFya/e0VSGExu/Xzy9Xcmtdq8HqHRoB2zQQsAAAAAAtq+82svT075mySF5Ma/T77zwXl9exu0AAAAALCegLYfHf67ye98ZOrxtR9Jvv/xeXvrcnEqoLVBCwAAAAAC2v71/D9MXnT+1ON/f09y85Xz8ral4amJAw1aAAAAABDQ9rcXvi35rf8x9fjq/zdZ/qW2v2WzQWuDFgAAAAAEtH2tUEh++33J885IapPJP/9hcvc32/qWjQatgBYAAAAABLQUCslJ/19yyCnJ5ETy+dOS+3/QtrcrDdcvCauaOAAAAAAAAS3JwGByyt8lz3pJsnYs+YffS/7r1ra8VaNB++DjY7nv0dG2vAcAAAAAbC8EtExZMJz87meSfV+QVFcnnzklefSelr/NIXstypKdR7LmqbU5+ZLr8v17Hm35ewAAAADA9kJAy3rDpeT/+Xyyx+FJ5dHkylcnj69s6VssHBrMP5/9WzliyU5ZPTaRN3z6hvyfH97f0vcAAAAAgO2FgJaNLVycnPbF5JnPStY8kHzm5OTJR1r6FrvtuDCf+6OjcvIRe2XtZC3v/tLtWfqV5Vm7brKl7wMAAAAA3U5Ay6Z22DV5w5eTxUuSx+5JrjolGXu8pW+xcGgw/9/vHZF3vPTXkiSXf39F3nj5jVk9NtHS9wEAAACAbiagZfMW75Oc/i9JedfkoduSz74uGa+09C0KhULeesKz8jenPS8jQ4P57t2P5jWfuC4rXB4GAAAAQJ8Q0LJluzxrau6guDj52Q+SL5yerB1v+du87NA9849veUH2XLww//nIaE7+xHX5/n+6PAwAAACA3iegZev2PDz5/S8kC0aSe76ZfOmPksl1LX+bQ/denC+/9eg8d8lOebwykTd86ob8ww9/1vL3AQAAAIBuIqBl2/Y9KnndVcnAULL8S8m//s+kVmv52+y2aGE+/0dH5ZXPnbo87M+/dFsuvNrlYQAAAAD0LgEt0/OslySn/n1SGEhuvjL5v+e3JaRdODSYv3rdEXnbbz8nSXLZdSvypit+lDVPuTwMAAAAgN4joGX6DjkleeX/nnr8/Y8n3724LW9TKBRy7oufnUt//3lZODSQa/7jkbzmE9/P/Y+5PAwAAACA3iKgZWae94bkxA9MPf72+5MbP9m2t3r5YXvmn97yW9lj0cLc8/CTefUl1+X6e///9u47vq273h//S8MalmzJe+8kbhJntdmjSdo0aVI6aKELSjeFC9wWCvTCr9yWCxS49N5vGYVCWzpvC4Veum6TlKRx9mymnR3biUe8LdmWrH1+f3w0bTmxE9tHtl/Px0MPSeccSceJpWO9zvvz/rQN2+sRERERERERERGNNAa0NHgLvwVc/T1x+/++Cxx+Z9heqizHhA++uQgzck2w2N348ku78de9nDyMiIiIiIiIiIjGBga0dGmW/3/A3K8CkIB/fA04sXbYXio9UYe/PrIAn5ueBY9PwhPvHsFPPjoKr2/oe+ASERERERERERGNJAa0dGkUCuD6XwLT7wAkL/DOvUD11mF7OV2cCr+9axa+vUJMHvbytmo89NpedHHyMCIiIiIiIiIiGsUY0NKlUyqBm58HStcAXifw9p1A/WfD9nIKhQKPrpiI5+8Wk4dtOiEmDzvXZh+21yQiIiIiIiIiIhpODGjp8qjigC+8AhQuAVzdwJu3Ac3Hh/Ulb5iehXceWYCMRC1ONXfj5ue3YTcnDyMiIiIiIiIiolGIAS1dvjgdcNfbQM5VQE8H8MYtQEfNsL7k9Fwz3v/GYkzPNaHD7saXX96Nd/bWDutrEhERERERERERDTUGtDQ0tAnAl/4OpE0Gus4Dr98MdDUO60tmmnT461cX4IbpWXB7JXz/3cP42f9x8jAiIiIiIiIiIho9GNDS0IlPBu75B2AuEBW0b3wesLcP60vqNSr87q5ZeGzFRADAi1ur8fDr+zh5GBERERERERERjQoMaGloJWYBX3kfMGYCzUeB//ki4Owe1pdUKBR4bMUk/O7uWdCqlfj0eDNu+8MO1LZz8jAiIiIiIiIiIoptDGhp6CUXiUpafRJQvw/4y92A2zHsL/u56dl455EFSE/Q4mRTN25+fjv21gxvBS8REREREREREdHlYEBLwyNjCvCldwGNEajeDLz7IOD1DPvLzsgz44NvLkZZTiLabS7c/eIu/G0fJw8jIiIiIiIiIqLYxICWhk/uVcCdbwEqLXD8I+CDbwI+37C/bKZJh789shBrpmXC7ZXwvb8fxs8/PsbJw4iIiIiIiIiIKOYoJEka06lVZ2cnTCYTrFYrEhMT5d6d8en4/wF/vQeQvMC8rwHX/wJQKIb9ZX0+Cc9tPIXfbDwFAFgxOR3P3TkLRq162F973OtsAGp3A+d2Aw0HxARymdOAzOni2pw/Ir8DRERERERERERyGEwmyYCWRsahvwL/+Kq4vfTfgOU/GLGX/uBQA777t0NweXy4IjMBL35lNvKS40fs9cc8rwdorgRq9wDndolr67kLP0Zn8oe1/sA2azqQOglQxY3MPhMRERERERERDSMGtGEY0MaQ3X8C1n5P3L7qfqB0DZA/T4R1w+xgrQUPv74PLV1OpBg0+OM9V2F2YfKwv+6Y5LACdftEhWztbnHb1R25jUIJZEwF8uYDOVcBDgvQeAQ4fxhoOQb4ovQjVmmB9Mn+wHaGuM4oA7TGEfmxiIiIiIiIiIiGCgPaMAxoY8zmXwGbfhq2QAFklgEFi4CChUD+QsCYNiwvfd7ag4de24fKhk5oVEo8c+s0fOGq3GF5rTFDkoCOGlEVW+uvjm2qBNDrY0OTAOTNEYFs3lwgdzagTYj+nB4n0HI8FNg2HhEXV1eUjRVAcrGosM2cBmT6g9uEjCH+QYmIiIiIiIiIhg4D2jAMaGOMJImetCfXAmd3AO1VfbdJmSjC2sDFnD9kL293efD4O4ewtqIRAPC1pSX4/qpSKJXshwoA8LiA84f81bH+QLa7qe92SYVA3rzQJX0yoFRd+uv6fIClJiyw9V93nY++vSE9LLT1t0pILgaUnPeQiIiIiIiIiOTHgDYMA9oY19UogtrApbmy7zamPCB/gT+wXQSkTrysCaZ8Pgn/b8NJ/PbT0wCA66Zk4Lk7ZsIwHicPs7WFWhXU7gbq9wNeZ+Q2yjgge2ZYIDsXSMgcmf3rbgmFtYHr1lPoU8ELABqjaIkQ6GmbOQ1InwKotSOzr0REREREREREfgxowzCgHWXs7SIoPLsdOLsTaDgASN7IbeJTgYIFIqzNXyCCuEuo3nz/YD2+9/fDwcnDXrp3NnKTxvDkYT4f0HYqNJFX7S6g7XTf7eJTQkFs3nwRzsbpR3x3++WyAU1HgcZDoTYJzUcBj6Pvtko1kFoaVm3rv+iTRn6/iYiIiIiIiGjcYEAbhgHtKOfsBur2Aud2igrbur19gzhtoggUA6Ft9qwBV00eONeBh1//DK3dTqQaNfjjPbNxVcEYCe9cdqBhfyiQrdsD9HT03S61VEzWljdPBLIpJZdVoSwLr0eEz41HRIuGQMVttJ8XAEz5vVokTANMuaPv5yYiIiIiIiKimMSANgwD2jHG4wQaDooK23M7Rfjo7IzcRq0Dcmb7WyIsAHLnAlpjv0/ZYBGThx09LyYP+8Vt03DrlaNw8rDOBlF9fM7frqDxMODzRG6j1gM5V4UC2dw5QHyyPPs73CQJ6Kzv1df2MGA5F317jRFIzBFBrSlHtNYI3s8FErNjq5KYiIiIYp/HBSiUgGocttIiIiIa5xjQhmFAO8b5vEBThWiHcHa7qLK1t0Zuo1CJYfr5gbYI8/uEknaXB9/+60GsrxQTYv3LshJ8d2UMTR7m84kg2mEFHBZx3WMRk2jV7RWhrDVK8JiQJYLY/PmiZUHmdEAVN9J7H1t6OoDGilBP2/OHgZbjfVtpRBOfGiW8zQES/SFuQublTZZGREREY0NnA7D7BWDfq4DGAKz8CVB2G0frEBERjSMMaMMwoB1nJEn0VQ30sD27I3pwmT7FX2G7EMhfCCRmweeT8F//PIHnN50BACydlIb7FhZi4YQUaNVDELp5nCJUDYSs4bf73Lf2ut+JqBNjhVMoxSRZ+fNDPWRNefwiMBBuB2CtBax14tJZ779f779dB7jtF38ehUpU2kYLbwPBrj6J/ydERERjVVMlsON3wJG/AT535LqCRcDq/wQyy+TZNyIiIhpRDGjDMKAlWGr9PWz9FbatJ/tuk1QUDGw/sRXjm+sscHnEWyNBq8a1k9Nx/dQMLC3QQe/t6idEvcj9aJNYDZZaD+jNgM4E6MyiEjhrpmhZkDP7gq0c6DJIkqi8DYa3db1u1wNdDX1bSkSj1vvD2tzI8DbRH+CackSlDREREY0OkgRUbwa2/wY4szG0vGARsOAbYjLTLf8FeHrECfXZDwLLfzh220wRERERAAa0ERjQUh/dLaFJx87tEMPcJV/EJu74dNQpc+DstiDe1w2TwoYE9ECpuNy3i8Ifrpr8Qas57LYp7H5Sr/v+6wFOfkYy8HmB7iYR1lprowe5tpaBPZc+KXp4m1Qg2lTE6Yb3ZyEiIqKL87qByn8AO34j/p4ERAA7+SZg4beA3NmhbS21wCdPAkffE/f1ycCKp4BZ97A9EhER0RjFgDYMA1q6KIcVqN0jAtuzO4D6z/oOSQvfXIqDFQZ0wQDozDCYUpCSmg6NMTl6qBp+X5MAKJUj9INRzHE7RFjbWe8PcuuAzrpQFa61DnB1Xfg5VFrxhS/QoiNvHituiYiIRpKjE9j/OrDrD+I4DgBx8cCsLwPz/wVILur/sVWbgbVPAC3HxP2smcCaZ4G8OcO+20RERDSyGNCGYUBLg+buESFtV2Oo2lVnhqRLRGWbAh8f78C6ikZUtdqCD1ErFVhQkoLVZVlYOTUDqUZWutIlclijh7ed9WIys95VuEq1+HJXsNA/Cd48UYFLREREQ6uzQYSyn70qJm8FAEMaMO8R0bZgoC0LvG5g70vApmdCzzPjbmDF00BCxnDsOREREcmAAW0YBrQ0HCRJwsmmbqytOI91FY043hiqelQqgLlFyVhdloVVUzORaeJwdBoch9uLBksPGiwONFh6UGfpQYOlBy63F3eWuDBfdQLKczv6mQRPISaLC1TYFiwCjGmy/BxERERjQmMFsDMw8Ze/33zqJGDBN4Hpd1x666HuZmDDj4GDb4r72kRg6RMi8FXFDc2+ExERkWwY0IZhQEsjoaqlG+sqG7GuohGH66wR667MN2N1WRauL8tEXnK8THtIsUKSJLTZXP4Atgf1FgfqO8TtBqu4bu12XfA5ilINuH9RIb5wVS7i7Q3A2Z3A2W0isG073fcBqZNCYW3BQtHbloiIiPonSUBVObDjt30n/lr4LWDiqqFrW1W3D/j4e0DDfnE/tRRY/UugZPnQPD8RERHJggFtGAa0NNLqOuxYVyHC2s/OdSD8HVaWkxgMa0vSjPLtJA0bh9uLRqvDH76KS3g1bL2lB06P76LPE69RIcesR7b/kpukR4fNhb/uq0WXQ1TvJOrUuGtePu5dUIhss148sKtJTH4X6KncVNH3yc35obC2YBGQXAwoFEP5z0BERDQ69Tfx15SbgQXfAnKvGp7X9flEJe2GHwP2VrFs8k3Aqp+J4zYRERGNOgxowzCgJTk1dzqwvrIRaysasauqDb6wd9ukDCOuL8vC6rJMXJGZAAUDspgnSRI67O5g0Npg6RHVr1ZRCdtg6UFLl/Oiz6NQAOkJ2lD4GhbEZpt1yDXHI1Gvjvo7YXN68PfP6vDK9mrUtNkBACqlAmumZeHBxUWYmWeOfIC9HTi3Czi7XQS25w8BkjdyG2NmZEuEtCs4mR0REY0vjk5g/2v+ib/qxbK4eGDWPcD8r1944q+h1GMByn8O7HlRHK/VemDxt4FF/wrE6UdmH4iIiGhIMKANw4CWYkVbtxP/PNqEtRWN2HGmFW5v6K1XmBIfDGun55oY1srE5fGh0eoIha+9rhssDvS4vRd9Hl2cMlj9mpukR7YpFMDmmPXINOmgUV9eAOrzSdh4vBkvb6vCrqr24PKrCpLw4OIirJySAbUqyms4u4DaPaEK2/p9gLdXSwV9EpDvD2wLFwEZ0wCV+rL2l4iIKCZZ64HdL/Sa+CsdmPfVwU38NdSaKoGPvy9aGAGiivb6XwClazjqhYiIaJRgQBuGAS3FImuPGxuPibB2y8mWiCHvOWY9ri/LxOqyTFyZnwSlkn+EXwqXxwdLjwtWuxuWHjcsdjcsdhesgds9Lljsblh73Oiwu9DS5URzlxMD+URM81e/5ph1EW0IcvwXc3zciIbslQ1W/HlbDT44VB8M/nPMety3sBB3zM1Dou4CE424e4D6z/yB7XYR3rrtkdtoEoD8eaEK2+xZgFo7jD8REdEY5uwW11q2OpJVY4XoL1vx98iJvxZ+C5h2+6VP/DWUJAmo/F/gkx+FqnpLrhX9aVMnyrtvREREdFEMaMMwoKVYZ3N6sOlEM9ZWNGLT8WbYXaEKzfQELVZNFWHt3KLk6BWRY5zD7Q2GqCJkdcPqD1cDwWvwvj9wtdhdsLkuXukajVatDAtddcgxx/uvxbIssw5atWqIf8qh0dzlwJs7z+LN3efQbhNVsQaNCl+cnYf7FxWiIMVw8SfxukUbhEBLhLM7AWfkxHdQ64DcOaE+trlzAA0nwCMi6lfHWeDkOuDEx0DNNgAK4IobgKvuBYqWsa3MSJEkoGqTf+KvT0PLCxb7J/5aGZv/Fy4bsPW/xH57XYAyTrRdWPp9QJsg994RERFRPxjQhmFAS6OJw+3FlpMtWFfRiH8eawpOBgUAyQYNrpucgeunZWJRSeplD5EfSZIkocftDYaogcrWjrDbvataA/cd7otPqNUfhQIw6eNg1sfBFK+BWR8Hc3wckuI1Ynm8/6LXIMWoQY5Zj2SDZtS3mHC4vXjvQD1e3laNU82iUkuhAK6bnIEHFxdhblHywH9Gn1cMswxU2J7dEZq8JECpBrKvDPWxTcwRXxgDF9UFKniJxjPLOTEZUeV74n1VsAgouQYoXgYY0+XeO7ocPh/QsB84sVZcmiv739aUD1x5DzDzS4ApZ+T2cTzxuoGK/xUBZ1Ovib8WfgvIGaaJv4Za2xlg/Q9F2A+IHvLX/Qcw/Xa2PSCi6Fw2QKGKjVEBROMQA9owDGhptHJ5fNhxphXrKhrxydGmYEUkACTo1FgxOQPXXJEOg1YFj1eC1yfB4wu/9oXue/tZHrbeJ0nw+HxRtg9b3uf5fFFe17/cK+57fBK6HR64vJcetKqUCn/IGucPWTVh9zWhoDUshDXrNUjQqcd1iwhJkrD1VCte3laNzSdbgsvLchLx4OIi3DAte/BBvyQBrafCKmy3h4Zd9ketjwxstQmANjHstjHKsijbqXX8Ahor3D2i+qx2D5A5DZiwAtCb5d6r0aGzQQSylf8L1O3tf7vMaSKsLbkGyJvPL1ajgcsOVJWLKtmT6wFbc2idQgnkLwBKVwOTVgOeHmD/68DhvwIOa2ibCSuAK+8FJq3iya2h0N/EX1d+RVSgJhXKunuX7OQnwLongPYqcT9vPrDmP4GsGfLu13hmb/efcPuHmOgtTicmdVPrxXXgEryvE7+Lav/1Be8HHsu/g+giJEl8LtTtFX+j1e4RJwjVOuCq+8UJqcQsufeSaFxhQBuGAS2NBR6vD3tq2rGuohHrKhrR3OWUe5cuSZxKERGimgLhauB+P1WuRq161Fe1yu10cxde3laD/91fF+x5nJ6gxb0LC3H33HwkGTSX9sSSBFjOhsLaun3iS4qzSwQQQ0mpjgxuNcaLBL/9LNMYY3MIa6xzdgGnPgGOfgCc+ifgtoXWKdWi+rN0jQigkgrk289Y1NUEHH1fhLLndoatUACFi4GpnxdBUfVm4MwmoPFw5OPVejFhX/FyEdimT+aX9FjR1ehvXbBWhLMeR2idJgGYuEIEshOviz7ZlLsHOPahCGtrtoaWG9KBmXeLIDGlZNh/jDHHWg/s/gPw2Wu9Jv56BJj9gHwTfw0ljxPY+Tyw5Veid7xCKQKYa54cGz/faOBxAac3AIfeFp8DvSddHQ6XFPhG2T4hE8iZzUlgRzuXDajfD9TtAWr3imC290i3cCqNGK2x+LHRe4KKaJRhQBuGAS2NNT6fhAO1HVh7pBF7z3YAANRKBVQKBVRKBdQq/7UycK2MvK/qZ7lSAZVSCZUSUCmVUbZXRC6PWN93uSrs9Y06Ncz6OMRrVAxaZdZuc+Gt3Wfx+s6zwaBfF6fErVfm4oFFRZiQPoST1njdItTrc+mMvO/q7rus9wVDfKhKKgImXAtMuA4oWgJoBtCfdzyyt4tqwGMfiuDQG3ZyyJQHFC4Rw7hbjkc+LqNMBLWla4CsmeMzELe1Asc+EMOqz24HpLBRBHnzgbJbxfDqhMy+j+1uEWHfmU/Fpbsxcr0xM1RdW7wMMKYN509C4SRJtH05sVa8Nxr2R6435ft/968XfU3Vgzj51XZGBLUH34qsvi1YLHrVTr5RBCvUv8YjwI7f9Zr4qxRY+M3YmfhrqFnrgX/+CKh4V9zXJwHX/Ai46j5AGZs980c1SQIaDgCH/iJ+z+xtoXUZZcCMO8VJNLdDnLBx28Vtt72f+z2hi6en133/dj5P//tzOXRm0Xe59HpRva8zDc/r0NCQJKCjJlQdW7dHTHYo9Zp3Q6URf3vlzRXzROTOAVqOAVueDZ0kVqiAaV8ElnwHSCsd6Z+EaFxhQBuGAS0RUV8ujw8fHW7Ay9uqUdnQGVy+rDQNDy4uwuIJqbETpvt8olqz35C3O3rw22fbzuhfclQa0Tt3wgpxSbtifFcndjWKQPbYh2Iyo/A//FMmAJNvEkFR9qzQv1PbmVCvzXM7IsPIhKxQWFu4ZGwGJAH2duD4RyKUrd4S+W+XM9sfyt4yuD6jkgQ0HxNBbdUmoGZ73+r0zOn+wHY52yEMB49TvBcClbLW2sj1OVeFfsfTp1z+54fXLVok7H8dOP3P0PtJZwKm3yGqajOnXd5rjCWBib+2/0ZcBxQsBhb9qzgRNx5OEtVsAz7+fqjfceZ0YM2vgPz58u7XWGGtAw6/I4LZ1hOh5cYMEXTNuHP43pded2RgGzXwjRbw9hP4unuAlhNAT3voNYIjYVYDk64HkouG52ehgXP3iJMBtbv91bF7AFtL3+0SsoG8OUDuXCBvHpA1HVBroz9nzXZg67NhkyQqgCk3AUseZ4sUomHCgDYMA1oiov5JkoQ91e14eVs1/nmsCYEjwqQMIx5YVIRbZuVAFzdGKnAkSQQtDitQ/5kIPk5tAKznIrdLzPVX164Q1Ym6cXDs6KgBjn0kKj5r9yCiYjljmvjjffKNAwuv7e2iFcKJj4HTG0WFdIDGKILE0jWix+ZYGIbrsALHPxbtC85sAnzu0LqsmaJ9wdTPD13bB7cDqN0Vqq5tPBK5PtAOIVBhO95POFyqiN/jTwFXV2idWi8+G0pXi9/jaFXQQ8VaJypq978R+VmVPUsEtWVfGB+fUdF0NYrPmF2/B5oqxDKFUpwEWfjN0TPx11DyeoB9LwObfhbqbTz9DjGR2HD+no5Vzm5xsvLQ2+KkW+DYqNYBV3wOmHGX+CwYjW0CfF5xvD/pP7naejJyfdpkUVk7aTWQO5vV2MNNksTEoRHVsUf6FhYo40SQGqiOzZsLmHIH/3r1nwFb/gs48X+hZRNXAku+C+TPu7yfhYgiMKANw4CWiGhgzrbZ8Mr2GvxtXy1sLlH5l2zQ4Mvz8vHlBQVITxiDVXmBSc9ObxCXmm2Rw/iValGNEGiHkDlt7IRdLSdEIHv0g749T3PniEB28o1AcvGlv4bHCVRvFSHXibVAV0NoXfikSaVrRlefTWcXcGKdCGVPb4jsO5hRFgplR+Jn6m4Gqjb33w4hIcvfCmE52yFcTOupUCV47a7ISnBjhqgqK10NFC0FNPEju28+H1BdLqpqj30UOhEQFw9MvVWEtXlzx87nU29eD9B81F9JtkdcW86G1scZgCvvGd0Tfw0lWyuw8cci2IckTo4t/T4w7+uDa7sxHvm8Iow99BdxjHTbQ+sKFotK2Sk3jb12AG1nQqMEzu6IHAESnypORk26XhxPtEPYDmu8cjuA8wdDYWztHqC7qe92xsxe1bEzhnaUTFMlsPW/xd8zgWNe4RLg6u+KY91YPaYQjSAGtGEY0BIRDY61x4139tbi1R01qLeIodQalRI3zsjGg4uLMCV7DH+WuuyiX+jpDWIirPYzkeuNGf5WCNeKwGs0VYBKEnD+kL99wQeR1TIKpRjaOPkmYPLngMTsYXr9g6La9MRaoKlX5WdqKXDFGhHW5syOvSHJLjtwar1oX3Dqk8jJoFJLRfuCqbcCaZPk28fwdghnPhVfsvtth3CNGPrc3zDI8cDrEUFfoIKs7XTk+kAv5UmrRcVqrPxO2lpFeLT/9cih1qmlIqidcSdgSJVv/4ZCT4eYdLJ2t7jUfRY5MSEAQCFaSpTdOnYm/hpq9fuBj78H1O8T91MmAqt/KY5hFKn5mKiUPfwO0HU+tDy5RFTKTr99/EyA2dMhqtNPrBWjjQLV2IBoC1W4JNQKwZwn336OJta6yFYF5w9HjrgBRFFA5vRe1bF5IxOStp0Btv0/cWwJ7FfObBHUTrqeQS3RZWBAG4YBLRHRpfF4fVhf2YSXt1Vh/zlLcPmC4hQ8uLgI11yRDqVyjP/B1l4lvqSc3iAqasIraRRK8cdroHdtLAU4AT6f+CIQCGUtYUOklXGiZ+nkG0UoOtKBjuVcaKKlmm2Rw/gMaf5qxTWi6nOkqxUD3A7x5bTyH6JiNjwgSi4JhbLpk2Pzy8uA2iEsDvWvHQ/tEBydwJmN4v/z1HoRRAQo48S/R+kaMbTXnC/ffg6EJImqq/2vid/RwOeTMk6caLnyK0DRstj7XOpNkkQ4Hghja/f0nXgQALSJ/tBinqgoy5k9fts7DIbPJ4LHDU+F+lde8Tlg1c9YbdzdIib6OvS2OIEZoDMDZbeJYDZ39tj/XLwQr1tMLHVinThed1RHrs+YJj4vS1cDWTH4d5AcPE7x+xSsjt0bOYIowJAeGcZmz5J/IkhLLbDjN+IEYOBEdEaZ6FE75Wa2uiC6BAxowzCgJSK6fAfOdeDlbdVYW9EIr08cNopSDbh/USFuuzIXBu0o7L82WB6nqEg8vUGEti3HItfHp4iga8J14lquoeRetwg8j30oJqwKHzIXFy/C5Mk3AZNWxs4QTYdVVCyfWCuunWHVOmq9CA8D1TrG9OHdF49LhJmV/yuqfcN7j5oLROuCsltFlcto+9Le3QxUlfsD2039t0MouUYE46O9CjPAci4ULtRsi6xa0if5ZzFfDZRcO3oDP4cVqHhXfKluOBBabs4HZt0DzPzS4CanG04um6jsDISxdXsig/KA5BJ/GOsf2ptWynDgcjisQPkvgd0viOHrah2w6FFg0WPynQSTg9shquYP/UUcbwJD+ZVqYOIqUYE+adX4Hl3QH0kSo29OrBXtEGp3R2kFs0qMOpDz5OpI62zwt17xf56dPxTZ+ggAFCrRJitvrr9dwRzxN0Ws/h3R3Qzs/B2w9+XQXAIpE4HF3xbV5Ko4efePaBRhQBuGAS0R0dCpt/Tg9R01eGvPOXQ5RMVjok6Nu+bl494Fhcg2y3zmfyRZakUl3ukNwJnyyCAPEBNETbxOBKI5s4d3EhG3Q8xefuxDEUKFhx3aRBFsTrlJBFCx/oXJ4wLO7RBfAI9/3GsSN4WoNCldDVxxA5A6aWi+3Hjdoo9r5T+A4x9GDudMzAWm3iJC2ewrY/fL1GD1aYewPbJtAyB63QX6146mdgg+H3D+QKifbGACqYCUCaHWBXnzRucEPxdy/jBw4A3g8F9Dv8sKpTh5dOVXRIAyUl+uJSlsaK+/d2zjkcj+loAIC3OuCgsv5o6dEwSxpvk4sPb7QPVmcd+UB6x6RoymGCufb71JkvjdO/Q2UPGPyJOA2VeKStmy2wBDinz7OBrZ2kTLn5Nro0ymqBMh7aTrxSUxS7bdvGzuHvE5Zjkr/vaznAOs/uuOs31PdgKib2/v6liNYeT3/XLZ24E9fwJ2/QFwWMQyUz6w+FFg5peHth8u0RjFgDYMA1oioqFnc3rw7v46/HlbNWraxLBalVKB1WWZWDopDcVpRpSkGWCOHyeTkXjdInw4vUEMie89lFxnEiFXoH/tUPR4dXaLL0bHPhTXgQoHQFTzXnEDMPlmoOjq0TspjCSJCSxOfCwu4ZWBgJjArNTft3awQZvXA5zdJnrKHvsQ6GkPrUvIEjPBT/28+HI1HoZsuh1iGGvVpujtEOLixb+FNiH64yOCHcUQLL/E5/C6RNgcXjmuUAJ58/0T0q0GUidG/xnGGnePmARw/+vidz3AkA7MvFuEtUM9kZ3HJSYdDG9XEN7PMyAhW8wUHqiQzZg2ej+nRiNJAo6+D3zypAiaAPF/kT1LBLbmfNFb1JQvevuO1uC2vVqcqDj0NtBRE1qemANMv0NUy6aVyrZ7Y4rHKUYonFwnRixEnFyF+N2atFq0Q4i1ESjO7lDgGrgE79cCtuYLP16hFG0Awqtjk4pi62e8XM4uUU2783ehVinGTGDhN4Gr7ufEcUQXwIA2DANaIqLh4/NJ+PR4M17eVo2dVW191icbNChONaA4zYDiNCOKUw0oSTciPzkecaoxHHp1NYZ61575NFR1EJBRJoLaCdeJL8UDDSZ6OkRF4LEPxfN7naF1CdmiAmrKTSKMGmtVgYAYRhioiqzeHDmEUJ8sKgNLV/tnmY4SJPq8IoSs/IcIJwJfMgDR93bKzaKnbP6C8RHKXkhEO4RPo88uHcs0RvEeK10jWhiM9wmkWk+LqtqDb0WGDQWLgavuFZ8dl9L7sLvF32PRH8Y2HOhbiR0+8U2gXYEp9/J+HhoaLruYGGj7ryOPJ+Hi4nuFtv7bpjxx35gZW5+XPRbg6HuihcG5naHlGqP4jJ9+h5jkKpb2eayRJKD5qP/k6jqg/jMAYZFDYm7oeF24ZPirMHsskYGr5ZwIkAP3w0/Q9keT0Pc9EDiJkVY6fgJKdw+w/w3xmdFZJ5bpk4H5XwfmfhXQm2XdvWHldYsTPao4UQihMY6tEJ6GDQPaMAxoiYhGRmWDFX/bV4eTTV2oarGhsdPR77ZqpQL5yfERwW1xmhHFaQakGDRQjKU/eHxe8eXk9AZxqd+P8C8qHnU8as1zcUQ/B9ukmThiM6HB0gOfJOG6KRn4QqkG85w7oTr+IVCzNXIyraQiEchOvkkM0xxPXzidXSI4DPTCC2/roNIARUtDfWutdaKnbOV7kUMR9ckimCq7VQRVYzHUHgqBL9v1+8N+/6TI9aE7/SxHP8ujbT/Y5+71OumTxZf+0dKSYSR53eL9sv918XkU6B+pM4ng6sqviD6J0fi8oi1GeO/Y9qq+2+mTI3vHZs+K/dYq453lnBiJEQisrLXiOtrQ7d5UGlGRGgiregdYiTnD31LD6xbHg0Nvi9Y4gbBZoRTD7GfcJUaVjMYh5mNBV5OYlPHEOjFKI3zC1ThDqM/8xFWD798vSWIYvuVslBDWf+3svPjz6Mzi99VcEPb76/8dNueL9WPpb9PL5XEBh/8iTvAEjgPaRGDOQ8CCb4z+FjUuuxjB1XhItA1qPAw0HY08kaXSiKBWnyxOAsen+C+9buvD7msM/D0ahxjQhmFAS0QkD5vTg+pWG860dKOqxYaqVhuq/Ld73N5+H5eoUwfD2pKw8LYgJR66uNifIEaSJHQ6PGiw9IQuVkfwtr2jCRNt+3C14iCuVh5GqiLyi8NpXzbKfTPQJCXhOtVnmK04CaUidKiW0qdAMfkmESxmTOUfeoBoV1C7W1TrHP+/vrNMh9OZgCtuBMo+L0JcTnRB45W1TlTU7n8jcjhy9izgyntFhVvzsVDv2Lp9fXttQyEC8eDQ3nmibQI/l8YGtwPorA8Lu8LCW8s5sa53P+HeFErRNiZQcRtefRsIdC+leluSxGRMh/4CVPw9ckRE2mRg5l3AtC8OTUuhMeRUUxf+tKUKrd1O3HplLlaXZUI9kiOa3D1A9VZxvD65rlcLlECf+etFO4T0yWJxd3PfqtfwADY88O1PfGqvCtiCyN/H0TpBpNy8HlGxvvW/xIlcQEzuetV9wMJvxc7klBfS0xEKYQPXrScjJ8ALiIsXJyv7G3FwMSptWICbHBbwpoRdkiLvx8XzmDrKMaANw4CWiCi2SJKExk4HqlpC4W3gusHa02/RnVIB5Cb5q25Tjf7qWxHipidoR6zq1uXxoanTgXp/4HreGrotLg50Oz0XfR61UoGsRA0WGhuwVHEQ0x17kd1VASX6/kF40FeM9d65WOebA29SCW6emY2bZ2ZjQno//UDHs8As08f/T1TX1u0Vw9CuuEH0lC25hr0uicL5fKKqbf/r4n3jc/e/rcYI5M4OVcjmzB7bQ1rpwrweEbCFh7bWXlW4Awky+oRn+ZFVuDpTaNvOBuDwOyKYbTkWWm5IE4HsjDtjr8dpDDhcZ8Hzm05jfWVku5ocsx73LyrEHXPykKAb4ROWgZD9xFox0dj5Q5HrDWmAo3Ngv0PGzF4nAPJDIawpl9XTw83nE/+HW34Vmi9AGQfM+hKw6DEguUjW3QMgft+6zoeFsf7q2N79kgMMaWKy1MzpQNZ0cR3oLey2i8pte5v/0i5aZQTv+5eFb3NZoW54dW6vQDdaBS9D3ZjCgDYMA1oiotHD4faiutUmKm5buiOqbrsuEHoatWoUBXrdhoW3xalG6DUDr7qVJAkddjcaLD2ot/TgvL/6NTyAbe5y9hsih0s2aJBl0iHbrEeOWY9ss7gduJ9q1EKl7PXHU0+H6Pt5aoPoE1lyDdyT1mBbix4fHGzA+spG2F2haqUpWYm4eWY2bpyRjWzzJVQgjQeOTjHUncPdiS7O1iqCr/2viRMdSUVh7QrmAulTAGXsj2SgGOHzicpWa22UKlx/kNunKjsKrclfaRsvTroF2pqotMAVa0QLg5JrOCKiF0mSsKe6Hb/bdBpbT7UGl18/NRMT0o14a885tNtEL/cErRp3zcvHfQsL5ft7orPBP8nYWqBqc2SrioTs6D1gzQWijcZw97GlgZEk0W5k63+JCTsBQKECpn0BWPwdIP2KkdkPn0+Mpjp/KDKMtbdG395c4A9hZ4TC2ITMoQs5Jckf6vYT3va0R1nXGjnXwmAplP6LKnRbqRI/U9TlyshLxLKwxwWXhz9eeZHX6+e15j0iQvAxjgFtGAa0RESjnyRJaOl2RlTbBgLc2nY7fBc4kuWY9f6wNtTnVqlQBKtdRQuCnmAI63BHGdLUi0atRLYpFLiK0DXsvkk/qGB4oOwuDzYca8YHB+tRfqIFHv8PrlAAcwuTcfPMHKyZlglzPCtEiegySJIYiszesWOKJElos7nQ6G+7c97qQIO1B41WBzxeCfOLk7GsNB15ySP0/y5JYhLN3qFteBWuve8EpMhfICplp9zCCu4oJElC+ckWPP/paew7K/qzq5QK3DwjG19fVoKJGWL0jcPtxf/ur8dL26pQ1WIDIEb33DA9Cw8vKUZZjqnf1xh2LptosWJIHZk+xjT0zu4AtjwLnNnoX6AAJn8OWPJdIHvm0L2O1w20HBcBbCCQbayIfvJHoQRSS0MhbNYM0Xc9Fj9HJEm8DyIC3F7BbnBdeKXuZYS6I+3Ot8VJtjGOAW0YBrRERGOb0+PFuTY7zrTYUNUaGd5a7BcYqnsBqUZtZODaK4CNhYnMOmwurK1oxHsH67GnOjQDcZxKgaWT0nDTzBxcNzljWIJiIiI5eX0SWrudaOlyQhenRFK8BiZ93Mj20owxkiTBYnfjvNWB81Yx+uO8RYSvDdYe/3IHXJ6Ln4QsTjVgaWkalpWmY15Rsrz93122UFhrawHy5wPJxfLtTwzz+iSsr2zE85tOo7JB9LfXqJT44uxcfG1pSb/Bu88nYdOJZry4tQq7qkJ/T8wvTsZDi4txzRXpUPYe8UM0UPX7RUXt8Y9CyyZcB1z9XfF+HgyXTUzedf5QKIxtPhY9lFTrxKiPrEAQOwPImHJpPa9HC0kCXN2if7jkEz3CJZ+4+MJuR13mFY+PWB7+eF+vbXs/hxRaftHn9S+ffJPoWz/GMaANw4CWiGj8are5UNXSHdbr1obq1m4ACGs9ELjokGPWI9Okg1Y9ukLNBksPPjzUgPcPNuDo+dCkY/EaFVZNzcRNM7OxeEIq4sZJeNHa7cSReisq6qzBf4+MRB3SErRIT9AiI1GH9EQtMhJ0MMfHyR62E1GI0+NFc6cT560ONHY60OgPF5s6RcDYaHWgucsJb5ShEyZ9HJLi42CO1yDZoIE5Pg7J8RokGTRIitcgKT4udNsQh6R4zaj4XAxMPhkMWy0ihA2EseK+44ITcAYoFECaUYsskw5ZJj2yzDpkm/RweX3YfLIFn53tiPi31cUpsaA4BctK07F0UhoKU9nLM9a4vT68f7ABvy8/HayEjdeo8KV5+XhoSTEyEgc+/L+i3oqXtlbho8Png6N0itMMeHBxEW67MndUTNZKMar5GLD1v8WkfoEJuAoWA1c/DhQv79tOwN4e1qIgMHnXKQRbnITTmsKqYv3XqZMAlXrYfyyii2FAG4YBLRERjSenmrrw/sEGvH+oHrXtPcHlyQYNbpiWhVtmZePK/KQxE0q2+cPYI3VWEcrWW9FgdQz48RqVUgS3iWHhbYIW6f7rwP2keA0riIguU7dThIyN/mAxPHQVYawDbbaBDc9UKoAUoxZOtxedjotPzNifBK0aZoMIcs19QlxxP7AuEPoOdUhlc3pE1as/eG2wOCIrXy09sLkuHr4CQIpBgyyzCF+zTTpkmfWhMNakQ0aiDhp1/6F0p8ON7adaUX6iBZtPtqCxM/LztDAlXoS1pWlYUJzCwE5GDrcXf9tXixc2V6HeIo73iTo17ltUhPsXFiLJcOntjhosPXhtRw3e2n0uOAdAskGDL88vwFcWFCDVyL7udInazgDbnwMOvh2alDLnKuDKeyMn8bLWRn+8MbNvGJtUyEmxKGYxoA3DgJaIiMYjSZJwoNaCDw424KPDDWjtDoUeuUl63DQjGzfPzEFpZoKMezk4gTC2ot4aDGWjhbEKBVCUasC0HBOm5ZgQp1KiucuBpk4nmrucaO4UFXjtAwyCANE6Is2oRVqiDhn+QDcjQecPdkPXKQYGuTT+BCZY7BO6hgWvjVbHBSd7DKdRK5Fl0iEzUYdMk/+SqBPLTHpkJuqQatQEWxp4vD5Yetyw2F1ot7nRYXehw+ZChz38duR9S497QBM+RhOvUUVU4ZrjNUjuXbkbFvI63V7R7zXYciBU+dpg7UHXAANmc3xcMHjN9PdBD4Sv2WYRvg5lYCpJEk40daH8RAvKTzRjX01HsKoSALRqJeYVp2DZpDQsK01DUaphzJz8i2XdTg/e3HUWL22tRmu3mEgr1ajFQ0uK8KV5+UjQDV2/1m6nB3/dW4s/b6sOhsAatRK3zsrBg4uLgv1siQbNWgfs+C3w2auAp58T60lFvfrFTgcSMkZ0N4kuFwPaMAxoiYhovPN4fdh+pg3vH6zH+orGiEqsKzITcPPMHNw4Iwu5SbEzIVC7zeUPYS3+ULYz+OWwt+JUA6blijC2LMeEqdmJA/qC6vL40NLtRFOnA82dTrQEQ9zIMHegFX2AmGAl1ahFRqIWaQm6iCA3IyzMTTFooWKQS6OAx+tDa7cL5/2TSQUD117VrwPpbQoACTp1MHgNhbB6ZJq0yEwUgeNItB7x+iR09vgDW7sLHTY32u2uYMgrrl2w2MO2sbujtlYYCgk6NbJNen/wGqp4zfa33sky6RCvkXe4bpfDjR1n2kR17YnmPifI8pPjsaw0DUsnpWFBSYrs+zvWdNhceGVHDV7bUQNrj6g8zDHr8cjSYtw+O29Yq5k9Xh/WVTbixa3VOFRrCS5fVpqGh5cUY2FJCsN5ujTdzcDO54FzO0V/6UAQm1kG6GScqI5oiDCgDcOAloiIKKTH5cWnx5vx3sF6lJ9ohtsb+jNgTmESbpqZgxumZSH5MoZGDlYgjK0Ia1VwoTC2zF8ZOy134GHs5XB5fGjtDgW2TV1OtHT2DXPbbM4BV+QpFfAHuaKFgjleA5USUCmV4lqhgFKpgFoprlWKyNuBdSqlAkqFuA5ewu4re91XKQGlQgG1Ugml/3XUqtBzKP33A68R/liNWolktnoYk7qdHtS02lDVKiZZrG614Wyb3d/v1YGBZpKpRk2w2jUzLHwNDK3PNOlg1I7e0C7QCzY8vG0PVuf6K3RtocC3wy62UasUwbA1vN1AljnUhmC0/btIkoRTzd0oP9GMzSdbsKe6PeJ4olErMa8oGUsnicnGStJYXXupmjsdeHFrFf5n9znY/SdYi1MN+PqyEtwyK2dE+yhLkoR9Zzvw4pYq/PNYU/CYNyUrEQ8tKcLnpmdfsIUGEdF4w4A2DANaIiKi6Kx2N9ZWnMf7Bxuwq7ot+EVLrVRgycRU3DIrBysmZ8AwhMFBR6AydgBhbJE/jJ0eqIzNSUTiMIexlyNQadjcqxK3d2VuW7dzwIFXrIlTKZCRKCYVyjKLwCk7OMRaDLM26TnxWixye32obbejutWGqhYRxla3ijC2qdN5wceqlApkJGjD2g34Q9ewKtj0RO2om2BxJEiSNC7eDzanx19d24zyEy19Ptdzk/TBsHZhScqQHlfGqtp2O17YfAZ/+6wuWKE+JSsR31g+AdeXZco+CqO61YZXtlfjb/vqghPUZSRqcd/CItw9Nx+m+Ng9XhMRjRQGtGEY0BIREV3ceWsPPjp0Hu8fqkdFfWdwuT5OheumZODmmdm4elLaoCp1LHYRxh6uC/WNreuIHsYWpsRjWq4Z03ISUeYPZGM5jL0cHq8P7TZXRGjb6RBDpwMXnyTB45PgCyyTItd5fWHrJcDr8/nXY0CP9UZb1+u+2B7w+Hzw+QC3zzegCmF9nArZ5lC1oAhx9aGJi8zyD9UeqyRJQnOXE1UtNn8QKwLY6lYbzrXbI/qH9pZq1KAo1YCiVAOK04woTIkPVnqmGNmSgwZOkiScaekOTjS2u6odLm+oBYZGpcScoqRgYDsx3TguQuyBOt3chd9vOoP3DzUEW2pcVZCEby6fgGWlaTH3b2Wxu/A/u8/h1R01aOkSJ3viNSrcPjsPDy4uQl5y7LRPIiIaaQxowzCgJSIiGpzTzd344GA93j/UgLNt9uDypPg4rJmWhZtn5mB2QVLEUPdAGBtoVXC47sJhbGSbAhNM+rEZxo4lHq8PzV3O4CzzDZae4MRHgeuB9usNTHaUE+i1adYhx6wPBoKZJt2IDtsdbboc7mDwGlEN22KL6DHdmz5OJULYNAOKUw0oTjOgKNWIohQDq91o2NhdHuz0964tP9mM2vbIY0OOWY+r/RONLZqQOuraPQyVI3VWPL/pNNYfbQyeDFsyMRXfWD4B84qSYy6Y7c3p8eKDgw14eVs1jjd2ARDtfFZNzcRDS4pxVUGSzHtIRHLx+iTYXR70uLyw+y+5yfoxW4wRjgFtGAa0REREl0aSJByqs+L9g/X48ND54GzRAJBt0uG6KRlo6XbiSL21zxfugIKUeBHE+i9TcxjGjmUOt1fMUm/pETPVW3rQ4A90A8Fut/PiM9YrFEB6gjZYcSsqcEU7hWyzCHRTDdox3Q/X5fHhnL8lQXVrd1gQawtWqUWjUiqQl6T3V8MaUewPY4vSDMhM1MV8yENjmyRJqG61+cPaFuyqaouYYE6tVGB2YRKWlaZjWWkaSjMSxvzv7J7qdvxu02lsOdkSXLZqaga+sXwCpuea5duxSyRJEraeasWLW6uw9VRrcPmV+WY8vKQYK6fK355hrJAkCTaXF23dTrTZXGjrdqHd5kRrt+iTHVjucHtDPeaVSqgUoZ73oid9qK+9SqGAShXqQa9W9upzH7aNOtC7PrhOGeyXH3Ed2EYV2VM//LnjNSoUphig5slZ2fh8EnrcIjztcXlhd3tgc/pvuzzBdTanP2h1i3U2pyd4OxDC2lyh+3aXF84oE4n++b7ZuOaKDBl+0pHFgDYMA1oiIqLL5/H6sLOqDe8fbMC6isaoIVt+cjym5YogdjrDWOpHp8ON8xaHP7jtibxtdeC8xRExHLo/GpUyOLt9cPIlsx5GrQpqpRJxKjEZmlqlQJxKfGlUqyKXq5X+df5lcSqxTWD5cIcIkiShqdOJqpbuYPgaaEtQ29ETHN4cTVqCVrQjCK+ETTUgPzmek/TQqNHj8mJXdRs2n2hB+Ylm1ISN2gCALJMOSyelYemkNCyamDpmqq0kScLmky14ftNp7K3pACBOrtw0IxtfX1aCSRkJMu/h0DjR2IWXtlbh/YMNwc/1/OR4PLCoEF+cncdexFHYXR60dbvQZguFrYHgNbC8zeZEe7cLrTZXxAmO0U4fp8K0XBNm5ZkxM8+MmflmZJn0cu/WqNHc6UBlQyeauxwiWHWHAlK7MxCoeoIVrIF1garWQC/p4aRQAPFxKsRr1fjlbdMY0PbCgJaIiIgGxeH2YtPxZuw404Zssx7Tc00oyzZxiDQNCZ9PQpvN1auVQlhFrsWB5i7HiEy0plAAcUoR1IYHvaFQt2/Aq1L2HwjH+a+tPW5UtdhQ02YLzsoejUGjQpE/fA0FsQYUphrGTFBFFK6m1YbyE83YfLIFO6va4HCHwielAv7WKHrkJOmDva5z/Jdssz7mAz+fT8L6ykY8X3462O9do1LiC7Nz8bWrS5CfMjb7tTZ3OfD6jrN4c/dZWOxuAECiTo0vzS/AfQsLkZGok3kPh4/D7fVXt0ZWuQbD1m4n2m2uYNXrpYRkujglUgxapBo1SDZokGLUIsWgQYpRg2SDFvEaVai/vTfUbz7Qrz7iOrCNzwevFH2b3r3s+13XaxvRLz+8b75/X7wSrD3uqC16MhK1mJErwtqZeWZMzzWP2zYoAZIkod7Sg4r6TlQ2iNZiFQ2dFxxdM1j6OBUMWhX0GhXi49TiWqNCvEbtvxbrDJrwdSroNWoY/OvCtw3c1qqVY35URG8MaMMwoCUiIiIaW9z+frgNlp4+vXB7XF64veLLn9snweP1weOV4PaJa4/XF7Hc45Pg8fng9srzJ7FaqUB+cnzEBF1F/jA2PUE77r7IEAU43F7srm4Xge2JFlS12i76GHN8HLJNIsAND26zzTrkJOlla43i9vrwwcEG/L78NM60iJ9DH6fCl+bl4+Gri8d0QBnO7vLg3c/q8PK26mC1dJxKgRtnZOOhxcWYkh2b39clSQz9tjlF1WG3U1Qedjs9sNhd/Yatbd3OC/YF749GrUSqP2hN9getKWH3U/3BayCEHQsTb/p8YnLBA7UWHKy14OA5C040dfUZSaJUABPTE4IVtjPzzJiUkTBm22b4fBJq2myoaOhEZb0VFQ1WVNR3wtrj7rOtUgGUpBmRlxzfJxgNhKe9lwfC1fCgVadWjekWUiONAW0YBrREREREdDFSWEWRu1eo6w0sC1sXCHUD23nDl4WtC90Wj/d4JcRrVMFq2LzkeE6IRjQAzZ0O1HaIkzL1/pMz9R2h252Oi/e31qiUwcrb8OpbUZErWqXo4lRDts8Otxd/+6wOf9x8JjhxZqJOjfsWFuK+RUVINmiG7LVGE69PwsZjTXhpazX21LQHly+akIKHlhRj2aS0Sz45JUkSnB5fsFemzeUJBqs2pycsZA0sC20XCF3tLg/sTm8wiLW5PLic1CROpUCK4SJhq1GDVIMWyUYNDBoVT85BBPoV9Z04WNsRDG0brI4+28VrVJiWY8LMfLO/PUISMk2j76SHx+vD6ZZuVNR3oqLeiqMNokI2Wsgfp1JgUkYCyrJNKMtJxJRsEyZnJYyJsH6sYUAbhgEtERERERHR2NblcKPB4kC9xY56f3uU+rBAt6lzYK1RUo1a5PgrbrNN/iA3rCLXHB930fCs2+nBW7vP4sWt1cFhx6lGDR5cXIwvz89HAluUBB2steClrVVYW9EYrJacmG7EVxYUIEEX5w9Y+w9W7S4PbIEw1h+oeoaxB45Bo4JBq4ZBKyoQk+I1Fw1eE7RqBq5DpLnTEVFle7jOEjXAzEzURVTZTssxxVQLFIfbi5NNXaE2BQ2dOH6+M+pkWro4JSZnJaIs24Sp2YkoyzFhYoYRWvXQnUyi4cOANgwDWiIiIiIiovHN7fWhqdMhQltroPrWEQxw6zt6BtT/Ux+n8rdMiBdBbrCNgh6pRi0+OtyAV7bXBIcgZ5t0eGRpCe6Ykzek1bljTV2HHa9sr8Ff99ZGnYj0UujilDBoQmFqIFg1+Id4G7VisqJg6KpRI14bum3QqoLLjFo1h37HIK9Pwunm7mCV7YFzFpxs6upzMkapACZlJGCWP7CdmZeECenGEWmNYHN6cOx8JyobOoP9Yk81dUU9kWDUqjElOzFYGVuWY0JxqgFqjrQZtRjQhmFAS0RERERERBciSWKiorpebRQaLA7U+W8PZhKe4lQDvrasBLfMzIFGzXBloDodbvx1Ty02HGtCnEoZFqz6w9JAcOoPXY3ayGXBkFWjHrN9SenCbE4PjtRbcbDWgkP+atvzUVojGDQqTA+bgGxWnhnpl9kP2mp3o/K8FZX1nf5+sVZUtdqitshIio9DWY4JUwNhbLYJ+cnxPAkwxjCgDcOAloiIiIiIiC6Xw+1Fo39SwrpggBsIcx04b+3BhHQjvra0BKvLshgQEsWIpk4HDpzzt0ao7cDhOivsUVojZJt0wcB2Zl4SpuWYoNdEr3xv7Xaiot4aVhlrRW17T9RtMxK1okVBjgll2YmYmmNCtknH1hfjAAPaMAxoiYiIiIiIiIgIEK0RTjV34WAwtI3eGkGlVKA0IwEz8swoy0lEU6cTlf5QtrGzb1UuAOQl6/0tCkyYkp2IqdmJSE8YfZOW0dBgQBuGAS0REREREREREfWn2+nBkTprsMr2YK0FTZ39tzVRKEQrE9GmIDCJlwmmeE4CSCGDySRjZxo7IiIiIiIiIiKiEWbUqrGgJAULSlKCy85be4JVtkfPdyIjUYeybDF51+SsRBi0jNRo6PC3iYiIiIiIiIiIKEyWSY+saXqsnpYl967QOMDpJImIiIiIiIiIiIhkwoCWiIiIiIiIiIiISCYMaImIiIiIiIiIiIhkwoCWiIiIiIiIiIiISCYMaImIiIiIiIiIiIhkwoCWiIiIiIiIiIiISCYMaImIiIiIiIiIiIhkwoCWiIiIiIiIiIiISCYMaImIiIiIiIiIiIhkwoCWiIiIiIiIiIiISCYMaImIiIiIiIiIiIhkwoCWiIiIiIiIiIiISCYMaImIiIiIiIiIiIhkwoCWiIiIiIiIiIiISCYMaImIiIiIiIiIiIhkwoCWiIiIiIiIiIiISCYMaImIiIiIiIiIiIhkwoCWiIiIiIiIiIiISCYMaImIiIiIiIiIiIhkwoCWiIiIiIiIiIiISCYMaImIiIiIiIiIiIhkwoCWiIiIiIiIiIiISCYMaImIiIiIiIiIiIhkwoCWiIiIiIiIiIiISCYMaImIiIiIiIiIiIhkwoCWiIiIiIiIiIiISCYMaImIiIiIiIiIiIhkwoCWiIiIiIiIiIiISCYMaImIiIiIiIiIiIhkwoCWiIiIiIiIiIiISCYMaImIiIiIiIiIiIhkwoCWiIiIiIiIiIiISCYMaImIiIiIiIiIiIhkwoCWiIiIiIiIiIiISCYMaImIiIiIiIiIiIhkwoCWiIiIiIiIiIiISCYMaImIiIiIiIiIiIhkwoCWiIiIiIiIiIiISCYMaImIiIiIiIiIiIhkwoCWiIiIiIiIiIiISCYMaImIiIiIiIiIiIhkwoCWiIiIiIiIiIiISCYMaImIiIiIiIiIiIhkwoCWiIiIiIiIiIiISCYMaImIiIiIiIiIiIhkwoCWiIiIiIiIiIiISCZquXdguEmSBADo7OyUeU+IiIiIiIiIiIhoPAhkkYFs8kLGfEDb1dUFAMjLy5N5T4iIiIiIiIiIiGg86erqgslkuuA2CmkgMe4o5vP50NDQgISEBCgUCrl3Z9h1dnYiLy8PtbW1SExMlHt3iEYFvm+ILg3fO0SDx/cN0aXhe4do8Pi+Ibo0Q/XekSQJXV1dyM7OhlJ54S6zY76CVqlUIjc3V+7dGHGJiYn8ACYaJL5viC4N3ztEg8f3DdGl4XuHaPD4viG6NEPx3rlY5WwAJwkjIiIiIiIiIiIikgkDWiIiIiIiIiIiIiKZMKAdY7RaLZ566ilotVq5d4Vo1OD7hujS8L1DNHh83xBdGr53iAaP7xuiSyPHe2fMTxJGREREREREREREFKtYQUtEREREREREREQkEwa0RERERERERERERDJhQEtEREREREREREQkEwa0RERERERERERERDJhQDtG7N27F2vWrIHZbIbBYMD8+fPxzjvvyL1bRDGrsLAQCoUi6mXZsmVy7x6RrN5880088sgjmD17NrRaLRQKBV599dV+t+/s7MR3vvMdFBQUQKvVorCwEN/73vfQ3d09cjtNFAMG8955+umn+z0OKRQK1NTUjOi+E8mlvr4ezz33HFauXIn8/HxoNBpkZmbitttuw+7du6M+hscdGu8G+77hMYdIcDgc+M53voOrr74a2dnZ0Ol0yMzMxKJFi/DKK6/A7Xb3ecxIHXPUQ/psJItNmzZh1apV0Ol0uPPOO5GQkIB3330Xd9xxB2pra/H444/LvYtEMclkMuGxxx7rs7ywsHDE94Uoljz55JM4e/YsUlNTkZWVhbNnz/a7rc1mw9KlS3Hw4EGsXLkSd911Fw4cOIBnn30WmzdvxpYtW6DT6UZw74nkM5j3TsC9994b9bhjNpuHfgeJYtBvf/tb/PKXv0RJSQlWrlyJtLQ0nDp1Cu+99x7ee+89vPXWW7jjjjuC2/O4QzT4900Ajzk03nV3d+MPf/gD5s6dixtuuAFpaWno6OjA2rVr8cADD+Avf/kL1q5dC6VS1LOO6DFHolHN7XZLJSUlklarlQ4cOBBcbrFYpEmTJkkajUaqqamRbweJYlRBQYFUUFAg924QxaR//vOfwWPHz3/+cwmA9Morr0Td9t///d8lANITTzwRsfyJJ56QAEjPPPPMcO8uUcwYzHvnqaeekgBImzZtGrkdJIpB7777rlReXt5n+ZYtW6S4uDgpKSlJcjgcweU87hAN/n3DYw6R4PV6JafT2We52+2Wli1bJgGQPvroo+DykTzmsMXBKPfpp5/izJkzuPvuuzFz5szgcpPJhB/+8IdwuVx47bXX5NtBIiIadVasWIGCgoKLbidJEl566SUYjUb86Ec/ilj3ox/9CEajES+99NJw7SZRzBnoe4eIQm699VYsXbq0z/IlS5Zg+fLl6OjowJEjRwDwuEMUMJj3DRGFKJVKaDSaPsvVajU+//nPAwBOnz4NYOSPOWxxMMqVl5cDAFauXNln3apVqwAAmzdvHsldIho1nE4nXn31VTQ0NCAxMRFz5szBvHnz5N4tolHj1KlTaGhowKpVq2AwGCLWGQwGLFq0COvXr0dtbS3y8vJk2kui2LZlyxbs3r0bSqUSEydOxIoVK2A0GuXeLaKYEBcXB0B8cQZ43CEaiN7vm3A85hBF5/P5sG7dOgBAWVkZgJE/5jCgHeVOnToFAJg4cWKfdZmZmTAajcFtiChSY2Mj7r///ohlc+bMwdtvv42SkhKZ9opo9LjQMSiwfP369Th16hS/KBP146mnnoq4bzab8etf/xpf+cpXZNojothw7tw5bNiwAVlZWZg2bRoAHneILiba+yYcjzlEgsvlwjPPPANJktDW1oaNGzfi+PHjuP/++3HttdcCGPljDlscjHJWqxWAaGkQTWJiYnAbIgq5//77sXHjRjQ1NcFms+HAgQO45557sHfvXlx77bXo6uqSexeJYt5AjkHh2xFRyIwZM/DnP/8ZVVVV6OnpQXV1NX77299CoVDgvvvuwwcffCD3LhLJxu1245577oHT6cQvf/lLqFQqADzuEF1If+8bgMccot5cLhd+/OMf4z/+4z/w/PPP48SJE/jud7+LP/3pT8FtRvqYwwpaIhqXep89njlzJl5//XUAwBtvvIEXX3wR3/nOd+TYNSIiGgcCfc4CCgsL8c1vfhOTJ0/GddddhyeffBI33XSTTHtHJB+fz4f77rsPW7ZswcMPP4x77rlH7l0iinkXe9/wmEMUyWg0QpIk+Hw+NDQ04MMPP8QPf/hD7Ny5Ex9//HEwfB1JrKAd5QJJfn+JfWdnZ79pPxH19cgjjwAAtm/fLvOeEMW+gRyDwrcjoou79tprUVJSgiNHjgTfQ0Tjhc/nwwMPPIC33noLX/7yl/HCCy9ErOdxh6ivi71vLoTHHBrvlEolcnNz8fWvfx1/+tOfsH37dvzsZz8DMPLHHAa0o1ygF0a0PrONjY3o7u7ut18GEfWVmpoKALDZbDLvCVHsu9AxKHw5j0NEgxM4Ftntdpn3hGjk+Hw+3H///Xjttddw11134dVXX4VSGfl1lccdokgDed9cDI85RMLKlSsBAOXl5QBG/pjDgHaUW7p0KQDgk08+6bNu/fr1EdsQ0cXt3r0bgBj2Q0QXNnHiRGRnZ2P79u19TmrYbDZs374dRUVFnKiFaBBsNhsqKythMBiCX5qJxrpAyPT666/jjjvuwBtvvBHRPzOAxx2ikIG+by6ExxyikIaGBgBAXFwcgJE/5jCgHeWuvfZaFBcX46233sLBgweDy61WK5555hloNBrOyEjUy/Hjx6OeIT5+/DieeOIJAMDdd9890rtFNOooFAo89NBD6O7uxk9+8pOIdT/5yU/Q3d2Nhx9+WKa9I4pdXV1dOHnyZJ/lPT09ePjhh9HV1YXbb78dajWni6CxLzA8+/XXX8cXv/hFvPnmm/2GTDzuEAmDed/wmEMUcvTo0ahZgN1uD85Bs2bNGgAjf8xRSJIkDdmzkSw2bdqEVatWQafT4c4770RCQgLeffddnD17Fs8++ywef/xxuXeRKKY8/fTT+O///m9cffXVKCgogMFgwMmTJ/Hxxx/D7XbjBz/4AZ555hm5d5NINi+99BK2bdsGADhy5Aj279+PRYsWYcKECQCAxYsX46GHHgIgzh4vWrQIhw4dwsqVK3HllVdi//79+OSTTzBnzhxs3rwZer1etp+FaCQN9L1TU1OD4uJizJkzB5MnT0ZmZiaampqwYcMG1NXVYdq0adi0aRNSUlLk/HGIRsTTTz+NH//4xzAajXj00UejhkS33HILZs6cCYDHHSJgcO8bHnOIQgJZwOLFi1FYWIjExETU19dj7dq1aGtrw5IlS7B+/frgcWREjzkSjQm7d++Wrr/+eikxMVHS6/XS3Llzpb/85S9y7xZRTCovL5duv/12aeLEiVJiYqKkVqulzMxM6eabb5bWr18v9+4Rye7ee++VAPR7uffeeyO2t1gs0mOPPSbl5eVJcXFxUn5+vvT4449LnZ2d8vwARDIZ6HvHarVK3/jGN6Q5c+ZIaWlpklqtlhISEqS5c+dK//mf/ynZ7XZ5fxCiEXSx9w0A6ZVXXol4DI87NN4N5n3DYw5RyN69e6WHH35Ymjp1qmQ2myW1Wi2lpKRIy5cvl/74xz9Kbre7z2NG6pjDCloiIiIiIiIiIiIimbAHLREREREREREREZFMGNASERERERERERERyYQBLREREREREREREZFMGNASERERERERERERyYQBLREREREREREREZFMGNASERERERERERERyYQBLREREREREREREZFMGNASERERERERERERyYQBLREREREREREREZFMGNASEREREQ2zmpoaKBQK3HfffXLvChERERHFGAa0RERERERERERERDJhQEtEREREREREREQkEwa0RERERERERERERDJhQEtEREREo86WLVtw4403IjU1FVqtFhMnTsSTTz4Ju90e3Ka8vBwKhQJPP/00tm3bhmXLliEhIQFmsxm33XYbTp8+HfW5KyoqcPvttyM9PR1arRZFRUV47LHH0NbWFnX75uZmPP744ygtLYVer0dycjLmzZuHZ599Nur2p0+fxuc//3kkJSXBYDBgxYoVOHTo0OX/oxARERHRqKSQJEmSeyeIiIiIiAbqD3/4A77xjW/AbDbjxhtvRHp6Ovbt24fy8nIsXLgQmzZtgkajQXl5OZYvX45Vq1Zh06ZNuP766zF16lRUVlbiww8/RGpqKnbt2oXi4uLgc2/btg2rVq2Cy+XCF77wBRQWFmLnzp3YvHkzSkpKsGvXLqSmpga3P3HiBJYvX47z589j8eLFWLhwIWw2GyorK3Ho0CG0t7cDEJOEFRUVYenSpaioqMDUqVMxe/ZsnDlzBu+//z6SkpJw7NgxZGRkjPi/JxERERHJiwEtEREREY0aR48exYwZMzB16lRs3LgRKSkpwXW/+MUv8IMf/ADPPvssHn/88WBACwAvvPACHnnkkeC2f/zjH/G1r30Nn/vc5/Dhhx8CAHw+HyZNmoQzZ85g3bp1WLVqVXD773//+/jVr36FBx54AC+//HJw+Zw5c7Bv3z786U9/wsMPPxyxr3V1dcjNzQUQCmgD+/nEE08Et/vRj36En/70p/j5z3+Of/u3fxuqfyoiIiIiGiUY0BIRERHRqPHoo4/iN7/5DbZs2YIlS5ZErPP5fMjMzER+fn6wonb58uWYNGkSjh07BqVSGbHtFVdcgdOnT6OpqQlpaWnYunUrrr76aqxevRoff/xxxHN3d3ejoKAAdrsdVqsVGo0Ge/bswbx583D11Vdj8+bNF9zvQEBbVFSE06dPR+xLYN2tt96Kd999dwj+lYiIiIhoNFHLvQNERERERAO1a9cuAMD69euxcePGPuvj4uJw/PjxiGWLFi2KCEQBQKlUYtGiRTh16hQOHTqEFStW4MCBAwCAZcuW9Xleo9GI2bNn45NPPsGJEycwbdo07NmzBwCwcuXKAe//zJkz++xLoMrWYrEM+HmIiIiIaOxgQEtEREREo0agp+vPfvazAT+mv76ugeVWqxUA0NnZecHts7KyIrYLPC4nJ2fA+5KYmNhnmVot/iT3er0Dfh4iIiIiGjuUF9+EiIiIiCg2BALOzs5OSJLU7yVcU1NT1OcKLDeZTBHP3d/2jY2NEduZzWYAQH19/WX8REREREQ03jGgJSIiIqJRY968eQBCrQ4GYvv27fD5fBHLfD4fduzYAYVCgRkzZgAAZs2aBQAoLy/v8xw2mw379u2DXq9HaWkpAGDu3LkAgE8++WTQPwcRERERUQADWiIiIiIaNf7lX/4FarUa3/rWt3Du3Lk+6y0WS7CXbMDJkyfx4osvRix78cUXcfLkSdxwww1IS0sDIHrVlpSUYO3atdiwYUPE9j/96U/R1taGu+66CxqNBgAwZ84czJkzB1u2bOnz/AAra4mIiIhoYNiDloiIiIhGjbKyMvz+97/H17/+dZSWlmLNmjUoKSlBV1cXqqqqsHnzZtx333144YUXgo9ZtWoV/vVf/xUff/wxpk6disrKSnz44YdITU3Fr3/96+B2SqUSr776KlatWoU1a9bgi1/8IgoKCrBz506Ul5ejpKQEv/jFLyL253/+53+wbNkyfPWrX8Ubb7yBBQsWwOFwoLKyEgcOHEBbW9uI/dsQERER0ejECloiIiIiGlUefvhh7Ny5E7fccgt27dqF5557Dn//+9/R2tqKb3/723jssccitp8/fz42btwIq9WK3/zmNygvL8ctt9yCnTt3ori4OGLbxYsXY9euXbj55pvxySef4Nlnn0V1dTUeffRR7Nq1K1htGzBx4kTs378fjz76KOrr6/Hcc8/hzTffRHd3N5588snh/qcgIiIiojFAIfWeRYGIiIiIaAwoLy/H8uXL8dRTT+Hpp5+We3eIiIiIiKJiBS0RERERERERERGRTBjQEhEREREREREREcmEAS0RERERERERERGRTNiDloiIiIiIiIiIiEgmrKAlIiIiIiIiIiIikgkDWiIiIiIiIiIiIiKZMKAlIiIiIiIiIiIikgkDWiIiIiIiIiIiIiKZMKAlIiIiIiIiIiIikgkDWiIiIiIiIiIiIiKZMKAlIiIiIiIiIiIikgkDWiIiIiIiIiIiIiKZ/P855v648wxVHwAAAABJRU5ErkJggg==\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "plot()"
      ],
      "metadata": {
        "id": "y408EL9-bZmm",
        "outputId": "6b43b15e-eadc-4a35-a186-4bf96187e8c9",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Normalisation des données"
      ],
      "metadata": {
        "collapsed": false,
        "id": "nrDcO65VbZmm"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "outputs": [],
      "source": [
        "X_titanic_scaled = titanic[features]\n",
        "scaler = MinMaxScaler()\n",
        "X_titanic_scaled = scaler.fit_transform(X_titanic_scaled)\n",
        "X_titanic_scaled = pd.DataFrame(X_titanic_scaled, columns=features)"
      ],
      "metadata": {
        "id": "OsM8TfQnbZmn"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "outputs": [],
      "source": [
        "X_titanic_scaled"
      ],
      "metadata": {
        "id": "avGhcfLWbZmo"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "outputs": [],
      "source": [
        "X_train, X_test, Y_train, Y_test = train_test_split(X_titanic_scaled, titanic['Survived'], random_state=0)"
      ],
      "metadata": {
        "id": "ScLIqSEdbZmp"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "outputs": [],
      "source": [
        "history = model.fit(X_train, Y_train, epochs=50, batch_size=10, validation_data=(X_test, Y_test), verbose=1)"
      ],
      "metadata": {
        "id": "E4qKPQkfbZmq"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "outputs": [],
      "source": [
        "plot()"
      ],
      "metadata": {
        "id": "KK_C2AZ1bZmr"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "outputs": [],
      "source": [
        "history = model.fit(X_train, Y_train, epochs=10, batch_size=350, validation_data=(X_test, Y_test), verbose=1)"
      ],
      "metadata": {
        "id": "8egnRmtabZms"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "outputs": [],
      "source": [
        "plot()"
      ],
      "metadata": {
        "id": "0xFTGkXhbZmt"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "outputs": [],
      "source": [
        "X_titanic_scaled = titanic[features]\n",
        "scaler = StandardScaler()\n",
        "X_titanic_scaled = scaler.fit_transform(X_titanic_scaled)\n",
        "X_titanic_scaled = pd.DataFrame(X_titanic_scaled, columns=features)"
      ],
      "metadata": {
        "id": "jxnkamEpbZmt"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "outputs": [
        {
          "data": {
            "text/plain": "       Pclass       Sex       Age     SibSp     Parch      Fare  Embarked\n0    0.908600 -0.756138 -0.527669  0.522511 -0.506787 -0.516380 -0.501226\n1   -1.482983  1.322511  0.577094  0.522511 -0.506787  0.694046  1.417445\n2    0.908600  1.322511 -0.251478 -0.552714 -0.506787 -0.503620 -0.501226\n3   -1.482983  1.322511  0.369951  0.522511 -0.506787  0.350326 -0.501226\n4    0.908600 -0.756138  0.369951 -0.552714 -0.506787 -0.501257 -0.501226\n..        ...       ...       ...       ...       ...       ...       ...\n707  0.908600  1.322511  0.646142 -0.552714  5.350885 -0.102875  3.336115\n708 -0.287191 -0.756138 -0.182430 -0.552714 -0.506787 -0.407687 -0.501226\n709 -1.482983  1.322511 -0.734812 -0.552714 -0.506787 -0.086335 -0.501226\n710 -1.482983 -0.756138 -0.251478 -0.552714 -0.506787 -0.086335  1.417445\n711  0.908600 -0.756138  0.162808 -0.552714 -0.506787 -0.506928  3.336115\n\n[712 rows x 7 columns]",
            "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Pclass</th>\n      <th>Sex</th>\n      <th>Age</th>\n      <th>SibSp</th>\n      <th>Parch</th>\n      <th>Fare</th>\n      <th>Embarked</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>0.908600</td>\n      <td>-0.756138</td>\n      <td>-0.527669</td>\n      <td>0.522511</td>\n      <td>-0.506787</td>\n      <td>-0.516380</td>\n      <td>-0.501226</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>-1.482983</td>\n      <td>1.322511</td>\n      <td>0.577094</td>\n      <td>0.522511</td>\n      <td>-0.506787</td>\n      <td>0.694046</td>\n      <td>1.417445</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>0.908600</td>\n      <td>1.322511</td>\n      <td>-0.251478</td>\n      <td>-0.552714</td>\n      <td>-0.506787</td>\n      <td>-0.503620</td>\n      <td>-0.501226</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>-1.482983</td>\n      <td>1.322511</td>\n      <td>0.369951</td>\n      <td>0.522511</td>\n      <td>-0.506787</td>\n      <td>0.350326</td>\n      <td>-0.501226</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>0.908600</td>\n      <td>-0.756138</td>\n      <td>0.369951</td>\n      <td>-0.552714</td>\n      <td>-0.506787</td>\n      <td>-0.501257</td>\n      <td>-0.501226</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>707</th>\n      <td>0.908600</td>\n      <td>1.322511</td>\n      <td>0.646142</td>\n      <td>-0.552714</td>\n      <td>5.350885</td>\n      <td>-0.102875</td>\n      <td>3.336115</td>\n    </tr>\n    <tr>\n      <th>708</th>\n      <td>-0.287191</td>\n      <td>-0.756138</td>\n      <td>-0.182430</td>\n      <td>-0.552714</td>\n      <td>-0.506787</td>\n      <td>-0.407687</td>\n      <td>-0.501226</td>\n    </tr>\n    <tr>\n      <th>709</th>\n      <td>-1.482983</td>\n      <td>1.322511</td>\n      <td>-0.734812</td>\n      <td>-0.552714</td>\n      <td>-0.506787</td>\n      <td>-0.086335</td>\n      <td>-0.501226</td>\n    </tr>\n    <tr>\n      <th>710</th>\n      <td>-1.482983</td>\n      <td>-0.756138</td>\n      <td>-0.251478</td>\n      <td>-0.552714</td>\n      <td>-0.506787</td>\n      <td>-0.086335</td>\n      <td>1.417445</td>\n    </tr>\n    <tr>\n      <th>711</th>\n      <td>0.908600</td>\n      <td>-0.756138</td>\n      <td>0.162808</td>\n      <td>-0.552714</td>\n      <td>-0.506787</td>\n      <td>-0.506928</td>\n      <td>3.336115</td>\n    </tr>\n  </tbody>\n</table>\n<p>712 rows × 7 columns</p>\n</div>"
          },
          "execution_count": 22,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "X_titanic_scaled"
      ],
      "metadata": {
        "id": "FdF-nW1pbZmu",
        "outputId": "6d2c8ec8-19ec-47a1-f391-03ae740918b6"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "outputs": [],
      "source": [
        "X_train, X_test, Y_train, Y_test = train_test_split(X_titanic_scaled, titanic['Survived'], random_state=0)"
      ],
      "metadata": {
        "id": "ITP5LYZxbZmv"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Epoch 1/50\n",
            "54/54 [==============================] - 0s 3ms/step - loss: 0.4880 - accuracy: 0.7828 - val_loss: 0.4826 - val_accuracy: 0.7640\n",
            "Epoch 2/50\n",
            "54/54 [==============================] - 0s 3ms/step - loss: 0.4301 - accuracy: 0.8034 - val_loss: 0.4769 - val_accuracy: 0.7865\n",
            "Epoch 3/50\n",
            "54/54 [==============================] - 0s 3ms/step - loss: 0.4098 - accuracy: 0.8258 - val_loss: 0.4817 - val_accuracy: 0.7921\n",
            "Epoch 4/50\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.3975 - accuracy: 0.8390 - val_loss: 0.4759 - val_accuracy: 0.8090\n",
            "Epoch 5/50\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.3983 - accuracy: 0.8315 - val_loss: 0.4687 - val_accuracy: 0.8146\n",
            "Epoch 6/50\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.3868 - accuracy: 0.8390 - val_loss: 0.4697 - val_accuracy: 0.8090\n",
            "Epoch 7/50\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.3783 - accuracy: 0.8446 - val_loss: 0.4682 - val_accuracy: 0.8202\n",
            "Epoch 8/50\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.3801 - accuracy: 0.8427 - val_loss: 0.4700 - val_accuracy: 0.8090\n",
            "Epoch 9/50\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.3758 - accuracy: 0.8427 - val_loss: 0.4771 - val_accuracy: 0.7921\n",
            "Epoch 10/50\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.3652 - accuracy: 0.8483 - val_loss: 0.4713 - val_accuracy: 0.8146\n",
            "Epoch 11/50\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.3715 - accuracy: 0.8521 - val_loss: 0.4746 - val_accuracy: 0.8258\n",
            "Epoch 12/50\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.3677 - accuracy: 0.8427 - val_loss: 0.4665 - val_accuracy: 0.8034\n",
            "Epoch 13/50\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.3630 - accuracy: 0.8464 - val_loss: 0.4758 - val_accuracy: 0.8034\n",
            "Epoch 14/50\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.3607 - accuracy: 0.8427 - val_loss: 0.4812 - val_accuracy: 0.8146\n",
            "Epoch 15/50\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.3577 - accuracy: 0.8521 - val_loss: 0.4849 - val_accuracy: 0.7865\n",
            "Epoch 16/50\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.3606 - accuracy: 0.8408 - val_loss: 0.4889 - val_accuracy: 0.8146\n",
            "Epoch 17/50\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.3620 - accuracy: 0.8446 - val_loss: 0.4809 - val_accuracy: 0.7978\n",
            "Epoch 18/50\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.3565 - accuracy: 0.8577 - val_loss: 0.4749 - val_accuracy: 0.8034\n",
            "Epoch 19/50\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.3561 - accuracy: 0.8502 - val_loss: 0.4869 - val_accuracy: 0.8090\n",
            "Epoch 20/50\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.3491 - accuracy: 0.8558 - val_loss: 0.4966 - val_accuracy: 0.7753\n",
            "Epoch 21/50\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.3500 - accuracy: 0.8596 - val_loss: 0.4939 - val_accuracy: 0.7978\n",
            "Epoch 22/50\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.3505 - accuracy: 0.8558 - val_loss: 0.4957 - val_accuracy: 0.7978\n",
            "Epoch 23/50\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.3439 - accuracy: 0.8689 - val_loss: 0.4953 - val_accuracy: 0.8090\n",
            "Epoch 24/50\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.3467 - accuracy: 0.8596 - val_loss: 0.5070 - val_accuracy: 0.7921\n",
            "Epoch 25/50\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.3497 - accuracy: 0.8652 - val_loss: 0.4966 - val_accuracy: 0.7865\n",
            "Epoch 26/50\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.3465 - accuracy: 0.8633 - val_loss: 0.5036 - val_accuracy: 0.7978\n",
            "Epoch 27/50\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.3458 - accuracy: 0.8633 - val_loss: 0.4989 - val_accuracy: 0.7809\n",
            "Epoch 28/50\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.3403 - accuracy: 0.8670 - val_loss: 0.5090 - val_accuracy: 0.7865\n",
            "Epoch 29/50\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.3370 - accuracy: 0.8652 - val_loss: 0.5093 - val_accuracy: 0.7921\n",
            "Epoch 30/50\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.3428 - accuracy: 0.8614 - val_loss: 0.5113 - val_accuracy: 0.7809\n",
            "Epoch 31/50\n",
            "54/54 [==============================] - 0s 3ms/step - loss: 0.3390 - accuracy: 0.8689 - val_loss: 0.5108 - val_accuracy: 0.7584\n",
            "Epoch 32/50\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.3424 - accuracy: 0.8670 - val_loss: 0.5168 - val_accuracy: 0.7753\n",
            "Epoch 33/50\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.3376 - accuracy: 0.8652 - val_loss: 0.5113 - val_accuracy: 0.7697\n",
            "Epoch 34/50\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.3390 - accuracy: 0.8633 - val_loss: 0.5195 - val_accuracy: 0.7921\n",
            "Epoch 35/50\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.3359 - accuracy: 0.8670 - val_loss: 0.5245 - val_accuracy: 0.7809\n",
            "Epoch 36/50\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.3330 - accuracy: 0.8633 - val_loss: 0.5241 - val_accuracy: 0.7753\n",
            "Epoch 37/50\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.3364 - accuracy: 0.8633 - val_loss: 0.5227 - val_accuracy: 0.7865\n",
            "Epoch 38/50\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.3394 - accuracy: 0.8577 - val_loss: 0.5167 - val_accuracy: 0.7809\n",
            "Epoch 39/50\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.3314 - accuracy: 0.8670 - val_loss: 0.5176 - val_accuracy: 0.7978\n",
            "Epoch 40/50\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.3319 - accuracy: 0.8670 - val_loss: 0.5169 - val_accuracy: 0.7753\n",
            "Epoch 41/50\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.3288 - accuracy: 0.8708 - val_loss: 0.5239 - val_accuracy: 0.7921\n",
            "Epoch 42/50\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.3316 - accuracy: 0.8633 - val_loss: 0.5209 - val_accuracy: 0.7753\n",
            "Epoch 43/50\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.3314 - accuracy: 0.8708 - val_loss: 0.5230 - val_accuracy: 0.7697\n",
            "Epoch 44/50\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.3315 - accuracy: 0.8670 - val_loss: 0.5329 - val_accuracy: 0.7640\n",
            "Epoch 45/50\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.3273 - accuracy: 0.8689 - val_loss: 0.5386 - val_accuracy: 0.7697\n",
            "Epoch 46/50\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.3285 - accuracy: 0.8745 - val_loss: 0.5306 - val_accuracy: 0.7753\n",
            "Epoch 47/50\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.3324 - accuracy: 0.8670 - val_loss: 0.5292 - val_accuracy: 0.7753\n",
            "Epoch 48/50\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.3336 - accuracy: 0.8670 - val_loss: 0.5334 - val_accuracy: 0.7640\n",
            "Epoch 49/50\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.3293 - accuracy: 0.8633 - val_loss: 0.5314 - val_accuracy: 0.7809\n",
            "Epoch 50/50\n",
            "54/54 [==============================] - 0s 2ms/step - loss: 0.3260 - accuracy: 0.8652 - val_loss: 0.5349 - val_accuracy: 0.7640\n"
          ]
        }
      ],
      "source": [
        "history = model.fit(X_train, Y_train, epochs=50, batch_size=10, validation_data=(X_test, Y_test), verbose=1)"
      ],
      "metadata": {
        "id": "JZVqwlsrbZmv",
        "outputId": "67e9ccd2-aaaa-4a40-aec7-0cd419b62580"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "outputs": [
        {
          "data": {
            "text/plain": "<Figure size 1700x1400 with 1 Axes>",
            "image/png": 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"
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "text/plain": "<Figure size 1700x1400 with 1 Axes>",
            "image/png": 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          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "plot()"
      ],
      "metadata": {
        "id": "VavHHsgIbZmv",
        "outputId": "617fc06c-a256-4d66-8540-d77cf50f1c3a"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Epoch 1/50\n",
            "9/9 [==============================] - 1s 26ms/step - loss: 0.6552 - accuracy: 0.6180 - val_loss: 0.6664 - val_accuracy: 0.5955\n",
            "Epoch 2/50\n",
            "9/9 [==============================] - 0s 6ms/step - loss: 0.6292 - accuracy: 0.6348 - val_loss: 0.6456 - val_accuracy: 0.6124\n",
            "Epoch 3/50\n",
            "9/9 [==============================] - 0s 6ms/step - loss: 0.6090 - accuracy: 0.6760 - val_loss: 0.6321 - val_accuracy: 0.6573\n",
            "Epoch 4/50\n",
            "9/9 [==============================] - 0s 6ms/step - loss: 0.5931 - accuracy: 0.6929 - val_loss: 0.6211 - val_accuracy: 0.6685\n",
            "Epoch 5/50\n",
            "9/9 [==============================] - 0s 6ms/step - loss: 0.5790 - accuracy: 0.7191 - val_loss: 0.6121 - val_accuracy: 0.6798\n",
            "Epoch 6/50\n",
            "9/9 [==============================] - 0s 6ms/step - loss: 0.5666 - accuracy: 0.7341 - val_loss: 0.6049 - val_accuracy: 0.6966\n",
            "Epoch 7/50\n",
            "9/9 [==============================] - 0s 6ms/step - loss: 0.5564 - accuracy: 0.7360 - val_loss: 0.5990 - val_accuracy: 0.6910\n",
            "Epoch 8/50\n",
            "9/9 [==============================] - 0s 6ms/step - loss: 0.5453 - accuracy: 0.7528 - val_loss: 0.5888 - val_accuracy: 0.6910\n",
            "Epoch 9/50\n",
            "9/9 [==============================] - 0s 6ms/step - loss: 0.5359 - accuracy: 0.7584 - val_loss: 0.5819 - val_accuracy: 0.7191\n",
            "Epoch 10/50\n",
            "9/9 [==============================] - 0s 6ms/step - loss: 0.5262 - accuracy: 0.7678 - val_loss: 0.5756 - val_accuracy: 0.7022\n",
            "Epoch 11/50\n",
            "9/9 [==============================] - 0s 6ms/step - loss: 0.5184 - accuracy: 0.7772 - val_loss: 0.5696 - val_accuracy: 0.7247\n",
            "Epoch 12/50\n",
            "9/9 [==============================] - 0s 6ms/step - loss: 0.5107 - accuracy: 0.7790 - val_loss: 0.5653 - val_accuracy: 0.7303\n",
            "Epoch 13/50\n",
            "9/9 [==============================] - 0s 6ms/step - loss: 0.5050 - accuracy: 0.7884 - val_loss: 0.5629 - val_accuracy: 0.7360\n",
            "Epoch 14/50\n",
            "9/9 [==============================] - 0s 6ms/step - loss: 0.4982 - accuracy: 0.7978 - val_loss: 0.5580 - val_accuracy: 0.7528\n",
            "Epoch 15/50\n",
            "9/9 [==============================] - 0s 5ms/step - loss: 0.4935 - accuracy: 0.8052 - val_loss: 0.5537 - val_accuracy: 0.7753\n",
            "Epoch 16/50\n",
            "9/9 [==============================] - 0s 5ms/step - loss: 0.4904 - accuracy: 0.8090 - val_loss: 0.5521 - val_accuracy: 0.7640\n",
            "Epoch 17/50\n",
            "9/9 [==============================] - 0s 6ms/step - loss: 0.4863 - accuracy: 0.8109 - val_loss: 0.5447 - val_accuracy: 0.7697\n",
            "Epoch 18/50\n",
            "9/9 [==============================] - 0s 6ms/step - loss: 0.4823 - accuracy: 0.8109 - val_loss: 0.5420 - val_accuracy: 0.7697\n",
            "Epoch 19/50\n",
            "9/9 [==============================] - 0s 6ms/step - loss: 0.4795 - accuracy: 0.8127 - val_loss: 0.5407 - val_accuracy: 0.7697\n",
            "Epoch 20/50\n",
            "9/9 [==============================] - 0s 6ms/step - loss: 0.4766 - accuracy: 0.8127 - val_loss: 0.5404 - val_accuracy: 0.7697\n",
            "Epoch 21/50\n",
            "9/9 [==============================] - 0s 6ms/step - loss: 0.4744 - accuracy: 0.8165 - val_loss: 0.5377 - val_accuracy: 0.7697\n",
            "Epoch 22/50\n",
            "9/9 [==============================] - 0s 6ms/step - loss: 0.4725 - accuracy: 0.8184 - val_loss: 0.5385 - val_accuracy: 0.7640\n",
            "Epoch 23/50\n",
            "9/9 [==============================] - 0s 6ms/step - loss: 0.4700 - accuracy: 0.8146 - val_loss: 0.5374 - val_accuracy: 0.7753\n",
            "Epoch 24/50\n",
            "9/9 [==============================] - 0s 5ms/step - loss: 0.4682 - accuracy: 0.8184 - val_loss: 0.5320 - val_accuracy: 0.7753\n",
            "Epoch 25/50\n",
            "9/9 [==============================] - 0s 6ms/step - loss: 0.4657 - accuracy: 0.8184 - val_loss: 0.5315 - val_accuracy: 0.7753\n",
            "Epoch 26/50\n",
            "9/9 [==============================] - 0s 6ms/step - loss: 0.4638 - accuracy: 0.8184 - val_loss: 0.5323 - val_accuracy: 0.7697\n",
            "Epoch 27/50\n",
            "9/9 [==============================] - 0s 6ms/step - loss: 0.4614 - accuracy: 0.8221 - val_loss: 0.5303 - val_accuracy: 0.7640\n",
            "Epoch 28/50\n",
            "9/9 [==============================] - 0s 6ms/step - loss: 0.4592 - accuracy: 0.8258 - val_loss: 0.5289 - val_accuracy: 0.7584\n",
            "Epoch 29/50\n",
            "9/9 [==============================] - 0s 6ms/step - loss: 0.4576 - accuracy: 0.8240 - val_loss: 0.5282 - val_accuracy: 0.7640\n",
            "Epoch 30/50\n",
            "9/9 [==============================] - 0s 6ms/step - loss: 0.4560 - accuracy: 0.8202 - val_loss: 0.5277 - val_accuracy: 0.7584\n",
            "Epoch 31/50\n",
            "9/9 [==============================] - 0s 6ms/step - loss: 0.4534 - accuracy: 0.8240 - val_loss: 0.5274 - val_accuracy: 0.7640\n",
            "Epoch 32/50\n",
            "9/9 [==============================] - 0s 6ms/step - loss: 0.4518 - accuracy: 0.8221 - val_loss: 0.5267 - val_accuracy: 0.7640\n",
            "Epoch 33/50\n",
            "9/9 [==============================] - 0s 6ms/step - loss: 0.4502 - accuracy: 0.8221 - val_loss: 0.5250 - val_accuracy: 0.7640\n",
            "Epoch 34/50\n",
            "9/9 [==============================] - 0s 6ms/step - loss: 0.4485 - accuracy: 0.8277 - val_loss: 0.5256 - val_accuracy: 0.7584\n",
            "Epoch 35/50\n",
            "9/9 [==============================] - 0s 6ms/step - loss: 0.4471 - accuracy: 0.8277 - val_loss: 0.5253 - val_accuracy: 0.7584\n",
            "Epoch 36/50\n",
            "9/9 [==============================] - 0s 6ms/step - loss: 0.4457 - accuracy: 0.8258 - val_loss: 0.5243 - val_accuracy: 0.7584\n",
            "Epoch 37/50\n",
            "9/9 [==============================] - 0s 6ms/step - loss: 0.4451 - accuracy: 0.8258 - val_loss: 0.5286 - val_accuracy: 0.7640\n",
            "Epoch 38/50\n",
            "9/9 [==============================] - 0s 6ms/step - loss: 0.4425 - accuracy: 0.8240 - val_loss: 0.5263 - val_accuracy: 0.7640\n",
            "Epoch 39/50\n",
            "9/9 [==============================] - 0s 6ms/step - loss: 0.4416 - accuracy: 0.8240 - val_loss: 0.5264 - val_accuracy: 0.7528\n",
            "Epoch 40/50\n",
            "9/9 [==============================] - 0s 6ms/step - loss: 0.4404 - accuracy: 0.8240 - val_loss: 0.5261 - val_accuracy: 0.7640\n",
            "Epoch 41/50\n",
            "9/9 [==============================] - 0s 6ms/step - loss: 0.4387 - accuracy: 0.8240 - val_loss: 0.5266 - val_accuracy: 0.7640\n",
            "Epoch 42/50\n",
            "9/9 [==============================] - 0s 6ms/step - loss: 0.4375 - accuracy: 0.8202 - val_loss: 0.5289 - val_accuracy: 0.7640\n",
            "Epoch 43/50\n",
            "9/9 [==============================] - 0s 6ms/step - loss: 0.4363 - accuracy: 0.8277 - val_loss: 0.5283 - val_accuracy: 0.7640\n",
            "Epoch 44/50\n",
            "9/9 [==============================] - 0s 6ms/step - loss: 0.4348 - accuracy: 0.8240 - val_loss: 0.5303 - val_accuracy: 0.7640\n",
            "Epoch 45/50\n",
            "9/9 [==============================] - 0s 7ms/step - loss: 0.4336 - accuracy: 0.8240 - val_loss: 0.5292 - val_accuracy: 0.7640\n",
            "Epoch 46/50\n",
            "9/9 [==============================] - 0s 6ms/step - loss: 0.4320 - accuracy: 0.8258 - val_loss: 0.5318 - val_accuracy: 0.7697\n",
            "Epoch 47/50\n",
            "9/9 [==============================] - 0s 6ms/step - loss: 0.4300 - accuracy: 0.8221 - val_loss: 0.5322 - val_accuracy: 0.7753\n",
            "Epoch 48/50\n",
            "9/9 [==============================] - 0s 6ms/step - loss: 0.4290 - accuracy: 0.8240 - val_loss: 0.5329 - val_accuracy: 0.7640\n",
            "Epoch 49/50\n",
            "9/9 [==============================] - 0s 5ms/step - loss: 0.4286 - accuracy: 0.8258 - val_loss: 0.5319 - val_accuracy: 0.7697\n",
            "Epoch 50/50\n",
            "9/9 [==============================] - 0s 6ms/step - loss: 0.4272 - accuracy: 0.8258 - val_loss: 0.5346 - val_accuracy: 0.7697\n"
          ]
        },
        {
          "data": {
            "text/plain": "<Figure size 1700x1400 with 1 Axes>",
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"
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "text/plain": "<Figure size 1700x1400 with 1 Axes>",
            "image/png": 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          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "model = Sequential()\n",
        "model.add(Dense(4, input_dim=7, activation='relu'))\n",
        "model.add(Dense(2, activation='relu'))\n",
        "model.add(Dense(1, activation='sigmoid'))\n",
        "opt = keras.optimizers.Adam(learning_rate=0.005)\n",
        "model.compile(loss='binary_crossentropy', optimizer=opt, metrics=['accuracy'])\n",
        "history = model.fit(X_train, Y_train, epochs=50, batch_size=60, validation_data=(X_test, Y_test), verbose=1)\n",
        "plot()"
      ],
      "metadata": {
        "id": "FMjtUWzVbZmw",
        "outputId": "8aa36400-17f3-4c0d-b602-7df0925af963"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "outputs": [],
      "source": [],
      "metadata": {
        "id": "Ps8Fw5fQbZmw"
      }
    }
  ],
  "metadata": {
    "kernelspec": {
      "name": "tensorflow",
      "language": "python",
      "display_name": "Python 3.10 (tensorflow)"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
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