redes-neuronales/Cuadernos/am_regresion_Keras_gasolina.ipynb

{"cells":[{"cell_type":"markdown","metadata":{"id":"6tE0_RFkVeuS"},"source":["<figure>\n","<img src=\"../Imagenes/logo-final-ap.png\"  width=\"80\" height=\"80\" align=\"left\"/>\n","</figure>\n","\n","# <span style=\"color:blue\"><left>Aprendizaje Profundo</left></span>"]},{"cell_type":"markdown","metadata":{"tags":[],"id":"NZT_fjLHVeuc"},"source":["# <span style=\"color:red\"><center>Diplomado en Ciencia de Datos</center></span>"]},{"cell_type":"markdown","metadata":{"id":"LJJJCkhUVeud"},"source":["# <span style=\"color:green\"><center>Regresion Basica con tf.keras: Predecir eficiencia de la gasolina</center></span>"]},{"cell_type":"markdown","metadata":{"id":"LPJ873IBVeue"},"source":["<figure>\n","<center>\n","<img src=\"https://raw.githubusercontent.com/AprendizajeProfundo/Alejandria/main/Redes_Neuronales/Imagenes/gasolina.jpg\" width=\"800\" height=\"400\" align=\"center\" />\n","</center>   \n","</figure>\n","<center>\n","\n","Fuente: <a href=\"https://commons.wikimedia.org/wiki/File:Dispensador_de_gasolina_viejo_en_San_Vicente.jpg\">Cesar Pérez</a>, <a href=\"https://creativecommons.org/licenses/by-sa/4.0\">CC BY-SA 4.0</a>, via Wikimedia Commons\n","\n","</center>"]},{"cell_type":"markdown","metadata":{"id":"8ivmaR7qVeuf"},"source":["## <span style=\"color:#4361EE\">Profesores</span>"]},{"cell_type":"markdown","metadata":{"id":"f6T4yittVeug"},"source":["* Alvaro  Montenegro, PhD, <ammontenegrod@unal.edu.co>\n","* Campo Elías Pardo, PhD, <cepardot@unal.edu.co>\n","* Daniel  Montenegro, Msc, <dextronomo@gmail.com>\n","* Camilo José Torres Jiménez, Msc, <cjtorresj@unal.edu.co>"]},{"cell_type":"markdown","metadata":{"id":"o4G7pLSUVeuh"},"source":["##   <span style=\"color:#4361EE\">Estudiantes auxiliares</span>"]},{"cell_type":"markdown","metadata":{"id":"KzNaIudLVeui"},"source":["* Jessica López, jelopezme@unal.edu.co\n","* Camilo Chitivo, cchitivo@unal.edu.co\n","* Daniel Rojas, anrojasor@unal.edu.co"]},{"cell_type":"markdown","metadata":{"id":"74TiXf72Veui"},"source":["## <span style=\"color:#4361EE\">Asesora Medios y Marketing digital</span>"]},{"cell_type":"markdown","metadata":{"id":"qSYs-qmdVeuj"},"source":["* Maria del Pilar Montenegro, pmontenegro88@gmail.com\n","* Jessica López Mejía, jelopezme@unal.edu.co"]},{"cell_type":"markdown","metadata":{"id":"oac1PobYVeuj"},"source":["## <span style=\"color:#4361EE\">Jefe Jurídica</span>"]},{"cell_type":"markdown","metadata":{"id":"Nar7oJClVeuj"},"source":["* Paula Andrea Guzmán, guzmancruz.paula@gmail.com"]},{"cell_type":"markdown","metadata":{"id":"5_idCP1CVeuj"},"source":["## <span style=\"color:#4361EE\">Coordinador Jurídico</span>"]},{"cell_type":"markdown","metadata":{"id":"H_xgQKvBVeuk"},"source":["* David Fuentes, fuentesd065@gmail.com"]},{"cell_type":"markdown","metadata":{"id":"vCu5VRKfVeuk"},"source":["## <span style=\"color:#4361EE\">Desarrolladores Principales</span>"]},{"cell_type":"markdown","metadata":{"id":"0ILDqN24Veuk"},"source":["* Dairo Moreno, damoralesj@unal.edu.co\n","* Joan Castro, jocastroc@unal.edu.co\n","* Bryan Riveros, briveros@unal.edu.co\n","* Rosmer Vargas, rovargasc@unal.edu.co\n","* Venus Puertas, vpuertasg@unal.edu.co"]},{"cell_type":"markdown","metadata":{"id":"RU2a2DQ8Veuk"},"source":["## <span style=\"color:#4361EE\">Expertos en Bases de Datos</span>"]},{"cell_type":"markdown","metadata":{"id":"g9B3kQhgVeu1"},"source":["* Giovvani Barrera, udgiovanni@gmail.com\n","* Camilo Chitivo, cchitivo@unal.edu.co"]},{"cell_type":"markdown","metadata":{"id":"p0zq66blVeu2"},"source":["## <span style=\"color:#4361EE\">Introducción</span>"]},{"cell_type":"markdown","metadata":{"id":"hrIqlTwFVeu2"},"source":["[Información general sobre Tensorflow](https://www.tensorflow.org/?hl=en).\n","\n","\n","<a target=\"_blank\" href=\"https://www.tensorflow.org/tutorials/keras/regression\"><img src=\"https://www.tensorflow.org/images/tf_logo_32px.png\" />Vea el cuaderno original en: TensorFlow.org</a>\n","\n","En un problema de *regresión*, buscamos predecir la salida de un valor continuo como la probabilidad de un precio. En contraste en un problema de *Clasificación*, buscamos seleccionar una clase de una lista de clases (por ejemplo, en donde una imagen contenga una manzana o una naranja queremos reconocer cual es la fruta en la imagen).\n","\n","En este cuaderno se usa el set de datos clásico [Auto MPG](https://archive.ics.uci.edu/ml/datasets/auto+mpg) y se construye un modelo para predecir la eficiencia de vehículos de 1970 y 1980. Para hacer esto proveeremos el modelo con una descripción de muchos automóviles de ese periodo. Esta descripción incluye atributos como: Cilindros, desplazamiento, potencia y peso.\n","\n","En el ejemplo usaremos el API *Sequential* de `tf.keras`."]},{"cell_type":"markdown","metadata":{"id":"4eYEQj95Veu3"},"source":["## <span style=\"color:#4361EE\">Importa librerías requeridas</span>"]},{"cell_type":"code","execution_count":1,"metadata":{"id":"1rRo8oNqZ-Rj","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1695330119047,"user_tz":300,"elapsed":5122,"user":{"displayName":"Camilo Jose Torres Jimenez","userId":"08254179589050810962"}},"outputId":"fdfc3bca-f582-4f4a-db30-e0b001235263"},"outputs":[{"output_type":"stream","name":"stdout","text":["2.13.0\n"]}],"source":["import tensorflow as tf\n","\n","from tensorflow import keras\n","from tensorflow.keras import layers\n","from tensorflow.keras.utils import plot_model\n","\n","import pathlib\n","\n","import matplotlib.pyplot as plt\n","import pandas as pd\n","import seaborn as sns\n","\n","print(tf.__version__)"]},{"cell_type":"markdown","metadata":{"id":"RCi3JUdiVeu5"},"source":["## <span style=\"color:#4361EE\">El conjunto de Datos MPG</span>"]},{"cell_type":"markdown","metadata":{"id":"F_72b0LCNbjx"},"source":["\n","El conjunto de datos MPG (millas por galón) está disponible en el siguiente repositorio [UCI Machine Learning Repository](https://archive.ics.uci.edu/ml/).\n"]},{"cell_type":"markdown","metadata":{"id":"gFh9ne3FZ-On"},"source":["## <span style=\"color:#4361EE\">Lectura de los datos</span>\n"]},{"cell_type":"markdown","metadata":{"id":"xl2LVTtoVeu6"},"source":["Primero descargamos e importamos el conjunto de datos usando Pandas."]},{"cell_type":"code","execution_count":2,"metadata":{"id":"CiX2FI4gZtTt","colab":{"base_uri":"https://localhost:8080/","height":206},"executionInfo":{"status":"ok","timestamp":1695330119881,"user_tz":300,"elapsed":838,"user":{"displayName":"Camilo Jose Torres Jimenez","userId":"08254179589050810962"}},"outputId":"38d60896-760e-448d-da28-d8077dea8005"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["      MPG  Cylinders  Displacement  Horsepower  Weight  Acceleration  \\\n","393  27.0          4         140.0        86.0  2790.0          15.6   \n","394  44.0          4          97.0        52.0  2130.0          24.6   \n","395  32.0          4         135.0        84.0  2295.0          11.6   \n","396  28.0          4         120.0        79.0  2625.0          18.6   \n","397  31.0          4         119.0        82.0  2720.0          19.4   \n","\n","     Model Year  Origin  \n","393          82       1  \n","394          82       2  \n","395          82       1  \n","396          82       1  \n","397          82       1  "],"text/html":["\n","  <div id=\"df-1788a045-dc55-488b-8caf-ad5c898a62f3\" class=\"colab-df-container\">\n","    <div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        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<td>24.6</td>\n","      <td>82</td>\n","      <td>2</td>\n","    </tr>\n","    <tr>\n","      <th>395</th>\n","      <td>32.0</td>\n","      <td>4</td>\n","      <td>135.0</td>\n","      <td>84.0</td>\n","      <td>2295.0</td>\n","      <td>11.6</td>\n","      <td>82</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>396</th>\n","      <td>28.0</td>\n","      <td>4</td>\n","      <td>120.0</td>\n","      <td>79.0</td>\n","      <td>2625.0</td>\n","      <td>18.6</td>\n","      <td>82</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>397</th>\n","      <td>31.0</td>\n","      <td>4</td>\n","      <td>119.0</td>\n","      <td>82.0</td>\n","      <td>2720.0</td>\n","      <td>19.4</td>\n","      <td>82</td>\n","      <td>1</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","    <div class=\"colab-df-buttons\">\n","\n","  <div class=\"colab-df-container\">\n","    <button class=\"colab-df-convert\" 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En la práctica de la vida diaria esto es algo que en general debe evitarse."]},{"cell_type":"code","execution_count":4,"metadata":{"id":"4ZUDosChC1UN","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1695330119885,"user_tz":300,"elapsed":13,"user":{"displayName":"Camilo Jose Torres Jimenez","userId":"08254179589050810962"}},"outputId":"285628f6-a7a1-4684-f271-813374c9a1ae"},"outputs":[{"output_type":"stream","name":"stdout","text":["Tamaño de los datos:  (392, 8)\n"]}],"source":["dataset = dataset.dropna()\n","print('Tamaño de los datos: ', dataset.shape)"]},{"cell_type":"markdown","metadata":{"id":"Xm4IJSQ5Veu8"},"source":["### <span style=\"color:#4CC9F0\">Codificación one-hot</span>\n"]},{"cell_type":"markdown","metadata":{"id":"8XKitwaH4v8h"},"source":["La columna de `\"Origin\"` realmente es categórica, no numérica. Entonces conviértala a un \"one-hot\":"]},{"cell_type":"code","execution_count":5,"metadata":{"id":"gWNTD2QjBWFJ","executionInfo":{"status":"ok","timestamp":1695330119886,"user_tz":300,"elapsed":12,"user":{"displayName":"Camilo Jose Torres Jimenez","userId":"08254179589050810962"}}},"outputs":[],"source":["# retira 'Origin' de dataset y lo entrega. Se recibe en la variable Origin\n","Origin = dataset.pop('Origin')"]},{"cell_type":"code","execution_count":6,"metadata":{"id":"ulXz4J7PAUzk","colab":{"base_uri":"https://localhost:8080/","height":206},"executionInfo":{"status":"ok","timestamp":1695330120168,"user_tz":300,"elapsed":293,"user":{"displayName":"Camilo Jose Torres Jimenez","userId":"08254179589050810962"}},"outputId":"f5e25f45-22d1-42e7-9768-fcf012ff48b3"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["      MPG  Cylinders  Displacement  Horsepower  Weight  Acceleration  \\\n","393  27.0          4         140.0        86.0  2790.0          15.6   \n","394  44.0          4          97.0        52.0  2130.0          24.6   \n","395  32.0          4         135.0        84.0  2295.0          11.6   \n","396  28.0          4         120.0        79.0  2625.0          18.6   \n","397  31.0          4         119.0        82.0  2720.0          19.4   \n","\n","     Model Year  USA  Europe  Japan  \n","393          82  1.0     0.0    0.0  \n","394          82  0.0     1.0    0.0  \n","395          82  1.0     0.0    0.0  \n","396          82  1.0     0.0    0.0  \n","397          82  1.0     0.0    0.0  "],"text/html":["\n","  <div id=\"df-5c9f3936-af76-4b85-941b-217911ffe9ec\" class=\"colab-df-container\">\n","    <div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>MPG</th>\n","      <th>Cylinders</th>\n","      <th>Displacement</th>\n","      <th>Horsepower</th>\n","      <th>Weight</th>\n","      <th>Acceleration</th>\n","      <th>Model Year</th>\n","      <th>USA</th>\n","      <th>Europe</th>\n","      <th>Japan</th>\n","  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test</span>"]},{"cell_type":"markdown","metadata":{"id":"Cuym4yvk76vU"},"source":["\n","Ahora divida el conjunto de datos en un conjunto de entrenamiento y otro de pruebas.\n","\n","Usaremos el conjunto de pruebas en la evaluación final de nuestro modelo."]},{"cell_type":"code","execution_count":7,"metadata":{"id":"qn-IGhUE7_1H","executionInfo":{"status":"ok","timestamp":1695330120169,"user_tz":300,"elapsed":6,"user":{"displayName":"Camilo Jose Torres Jimenez","userId":"08254179589050810962"}}},"outputs":[],"source":["train_dataset = dataset.sample(frac=0.8,random_state=0)\n","test_dataset = dataset.drop(train_dataset.index)"]},{"cell_type":"code","execution_count":8,"metadata":{"id":"DtSQXOnYVevA","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1695330120169,"user_tz":300,"elapsed":6,"user":{"displayName":"Camilo Jose Torres Jimenez","userId":"08254179589050810962"}},"outputId":"051ff527-3862-4aeb-9d28-232251616bc0"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["Index(['MPG', 'Cylinders', 'Displacement', 'Horsepower', 'Weight',\n","       'Acceleration', 'Model Year', 'USA', 'Europe', 'Japan'],\n","      dtype='object')"]},"metadata":{},"execution_count":8}],"source":["train_dataset.keys()"]},{"cell_type":"markdown","metadata":{"id":"CLh0MquOVevA"},"source":["### <span style=\"color:#4CC9F0\">Descriptivo de los datos</span>\n"]},{"cell_type":"markdown","metadata":{"id":"J4ubs136WLNp"},"source":["\n","Revise rápidamente la distribución conjunta de cada par de columnas del conjunto de entrenamiento."]},{"cell_type":"code","execution_count":9,"metadata":{"id":"oRKO_x8gWKv-","colab":{"base_uri":"https://localhost:8080/","height":1000},"executionInfo":{"status":"ok","timestamp":1695330130585,"user_tz":300,"elapsed":10420,"user":{"displayName":"Camilo Jose Torres Jimenez","userId":"08254179589050810962"}},"outputId":"7bcd774a-a7f6-43ed-99be-5a3f1c202b75"},"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 1000x1000 with 20 Axes>"],"image/png":"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\n"},"metadata":{}}],"source":["sns.pairplot(train_dataset[[\"MPG\", \"Cylinders\", \"Displacement\", \"Weight\"]], diag_kind=\"kde\")\n","plt.show()"]},{"cell_type":"markdown","metadata":{"id":"gavKO_6DWRMP"},"source":["También revise las estadisticas descriptivas generales:"]},{"cell_type":"code","execution_count":10,"metadata":{"id":"yi2FzC3T21jR","colab":{"base_uri":"https://localhost:8080/","height":332},"executionInfo":{"status":"ok","timestamp":1695330130587,"user_tz":300,"elapsed":19,"user":{"displayName":"Camilo Jose Torres Jimenez","userId":"08254179589050810962"}},"outputId":"f795d621-98f6-4448-b9d2-dc34582160ac"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["              count         mean         std     min      25%     50%  \\\n","Cylinders     314.0     5.477707    1.699788     3.0     4.00     4.0   \n","Displacement  314.0   195.318471  104.331589    68.0   105.50   151.0   \n","Horsepower    314.0   104.869427   38.096214    46.0    76.25    94.5   \n","Weight        314.0  2990.251592  843.898596  1649.0  2256.50  2822.5   \n","Acceleration  314.0    15.559236    2.789230     8.0    13.80    15.5   \n","Model Year    314.0    75.898089    3.675642    70.0    73.00    76.0   \n","USA           314.0     0.624204    0.485101     0.0     0.00     1.0   \n","Europe        314.0     0.178344    0.383413     0.0     0.00     0.0   \n","Japan         314.0     0.197452    0.398712     0.0     0.00     0.0   \n","\n","                  75%     max  \n","Cylinders        8.00     8.0  \n","Displacement   265.75   455.0  \n","Horsepower     128.00   225.0  \n","Weight        3608.00  5140.0  \n","Acceleration    17.20    24.8  \n","Model Year      79.00    82.0  \n","USA              1.00     1.0  \n","Europe           0.00     1.0  \n","Japan            0.00     1.0  "],"text/html":["\n","  <div id=\"df-a68566a5-963f-41b0-8c99-1f16a7402a9f\" class=\"colab-df-container\">\n","    <div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n"," 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     <td>455.0</td>\n","    </tr>\n","    <tr>\n","      <th>Horsepower</th>\n","      <td>314.0</td>\n","      <td>104.869427</td>\n","      <td>38.096214</td>\n","      <td>46.0</td>\n","      <td>76.25</td>\n","      <td>94.5</td>\n","      <td>128.00</td>\n","      <td>225.0</td>\n","    </tr>\n","    <tr>\n","      <th>Weight</th>\n","      <td>314.0</td>\n","      <td>2990.251592</td>\n","      <td>843.898596</td>\n","      <td>1649.0</td>\n","      <td>2256.50</td>\n","      <td>2822.5</td>\n","      <td>3608.00</td>\n","      <td>5140.0</td>\n","    </tr>\n","    <tr>\n","      <th>Acceleration</th>\n","      <td>314.0</td>\n","      <td>15.559236</td>\n","      <td>2.789230</td>\n","      <td>8.0</td>\n","      <td>13.80</td>\n","      <td>15.5</td>\n","      <td>17.20</td>\n","      <td>24.8</td>\n","    </tr>\n","    <tr>\n","      <th>Model Year</th>\n","      <td>314.0</td>\n","      <td>75.898089</td>\n","      <td>3.675642</td>\n","      <td>70.0</td>\n","      <td>73.00</td>\n","      <td>76.0</td>\n","      <td>79.00</td>\n","      <td>82.0</td>\n","    </tr>\n","    <tr>\n","      <th>USA</th>\n","      <td>314.0</td>\n","      <td>0.624204</td>\n","      <td>0.485101</td>\n","      <td>0.0</td>\n","      <td>0.00</td>\n","      <td>1.0</td>\n","      <td>1.00</td>\n","      <td>1.0</td>\n","    </tr>\n","    <tr>\n","      <th>Europe</th>\n","      <td>314.0</td>\n","      <td>0.178344</td>\n","      <td>0.383413</td>\n","      <td>0.0</td>\n","      <td>0.00</td>\n","      <td>0.0</td>\n","      <td>0.00</td>\n","      <td>1.0</td>\n","    </tr>\n","    <tr>\n","      <th>Japan</th>\n","      <td>314.0</td>\n","      <td>0.197452</td>\n","      <td>0.398712</td>\n","      <td>0.0</td>\n","      <td>0.00</td>\n","      <td>0.0</td>\n","      <td>0.00</td>\n","      <td>1.0</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","    <div class=\"colab-df-buttons\">\n","\n","  <div class=\"colab-df-container\">\n","    <button 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Esta etiqueta es el valor que entrenará el modelo para predecir."]},{"cell_type":"code","execution_count":11,"metadata":{"id":"t2sluJdCW7jN","executionInfo":{"status":"ok","timestamp":1695330130590,"user_tz":300,"elapsed":17,"user":{"displayName":"Camilo Jose Torres Jimenez","userId":"08254179589050810962"}}},"outputs":[],"source":["train_labels = train_dataset.pop('MPG')\n","test_labels = test_dataset.pop('MPG')"]},{"cell_type":"markdown","metadata":{"id":"mRklxK5s388r"},"source":["### <span style=\"color:#4CC9F0\">Normalice los datos</span>\n"]},{"cell_type":"markdown","metadata":{"id":"1Gvs3Jo7VevC"},"source":["Revise otra vez el bloque de `train_stats` que se presentó antes y note la diferencia de rangos de cada característica."]},{"cell_type":"markdown","metadata":{"id":"-ywmerQ6dSox"},"source":["Es una buena práctica normalizar variables que utilizan diferentes escalas y rangos. Aunque el modelo *podría* converger sin normalización de características, dificulta el entrenamiento y hace que el modelo resultante dependa de la elección de las unidades utilizadas en la entrada."]},{"cell_type":"markdown","metadata":{"id":"MKId63yGVevC"},"source":["### <span style=\"color:#4CC9F0\">Nota</span>"]},{"cell_type":"markdown","metadata":{"id":"6sznlLScVevC"},"source":["Aunque generamos intencionalmente estas estadísticas solo del conjunto de datos de entrenamiento, estas estadísticas también se utilizarán para normalizar el conjunto de datos de prueba. Necesitamos hacer eso para proyectar el conjunto de datos de prueba en la misma distribución en la que el modelo ha sido entrenado."]},{"cell_type":"code","execution_count":12,"metadata":{"id":"JlC5ooJrgjQF","executionInfo":{"status":"ok","timestamp":1695330130593,"user_tz":300,"elapsed":19,"user":{"displayName":"Camilo Jose Torres Jimenez","userId":"08254179589050810962"}}},"outputs":[],"source":["# función para normalizar los datos.\n","def norm(x):\n","  return (x - train_stats['mean']) / train_stats['std']\n","\n","# normaliza los datos\n","normed_train_data = norm(train_dataset)\n","normed_test_data = norm(test_dataset)"]},{"cell_type":"code","execution_count":13,"metadata":{"id":"oimsUorfVevD","colab":{"base_uri":"https://localhost:8080/","height":332},"executionInfo":{"status":"ok","timestamp":1695330130933,"user_tz":300,"elapsed":357,"user":{"displayName":"Camilo Jose Torres Jimenez","userId":"08254179589050810962"}},"outputId":"ac159a05-9341-481b-a9b5-5f894f1e9da6"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["              count          mean  std       min       25%       50%  \\\n","Cylinders     314.0  1.824443e-16  1.0 -1.457657 -0.869348 -0.869348   \n","Displacement  314.0  8.627211e-17  1.0 -1.220325 -0.860894 -0.424785   \n","Horsepower    314.0 -9.900078e-18  1.0 -1.545283 -0.751241 -0.272190   \n","Weight        314.0 -8.485781e-17  1.0 -1.589352 -0.869478 -0.198782   \n","Acceleration  314.0 -5.148041e-16  1.0 -2.710152 -0.630725 -0.021237   \n","Model Year    314.0  9.772791e-16  1.0 -1.604642 -0.788458  0.027726   \n","USA           314.0  7.920062e-17  1.0 -1.286751 -1.286751  0.774676   \n","Europe        314.0  1.980016e-17  1.0 -0.465148 -0.465148 -0.465148   \n","Japan         314.0  5.374328e-17  1.0 -0.495225 -0.495225 -0.495225   \n","\n","                   75%       max  \n","Cylinders     1.483887  1.483887  \n","Displacement  0.675074  2.489002  \n","Horsepower    0.607162  3.153347  \n","Weight        0.732017  2.547401  \n","Acceleration  0.588250  3.313017  \n","Model Year    0.843910  1.660094  \n","USA           0.774676  0.774676  \n","Europe       -0.465148  2.143005  \n","Japan        -0.495225  2.012852  "],"text/html":["\n","  <div id=\"df-583ff773-849c-4f8d-8f3d-9cff7eacd344\" class=\"colab-df-container\">\n","    <div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>count</th>\n","      <th>mean</th>\n","      <th>std</th>\n","      <th>min</th>\n","      <th>25%</th>\n","      <th>50%</th>\n","      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Eso incluye el conjunto de pruebas, así como los datos en vivo cuando el modelo se usa en producción."]},{"cell_type":"markdown","metadata":{"id":"6SWtkIjhrZwa"},"source":["## <span style=\"color:#4361EE\">Modelo matemático</span>"]},{"cell_type":"markdown","metadata":{"id":"JjUVkX7DVevD"},"source":["### <span style=\"color:#4CC9F0\">Función predictora</span>"]},{"cell_type":"markdown","metadata":{"id":"wlDwf2X1VevE"},"source":["Supongamos que $\\mathbf{x}_i \\in \\mathbb{R}^n$ representa al vector de datos de la muestra $i$ y que  $y_i$ es la respectiva etiqueta. El modelo predictivo es una red neuronal, la cual es una función $\\text{rn}:\\mathbb{R}^n \\to \\mathbb{R}$, con parámetros $\\mathbf{w},b$. La predicción asociada a $\\mathbf{x}_i$ se denota $\\hat{y}_i$ y se define por\n","\n","$$\n","\\hat{y}_i = \\text{rn}(\\mathbf{x}_i).\n","$$\n","\n","Para cualquier vector $\\mathbf{x}$ en el espacio de características, su predicción se denota por $\\hat{y} = \\text{rn}(\\mathbf{x})$."]},{"cell_type":"markdown","metadata":{"id":"3RC3yKUQVevE"},"source":["### <span style=\"color:#4CC9F0\">Función de pérdida</span>"]},{"cell_type":"markdown","metadata":{"id":"vCjj8moCVevE"},"source":["La función predictiva tiene parámetros $\\mathbf{w},b$, por lo que podemos denotarla de manera más genérica como $\\text{rn}(\\mathbf{x}|\\mathbf{w},b)$. Si se tienen $n$ datos de entrenamiento, la función de pérdida error cuadrático medio (MSE)  es dada por\n","\n","$$\n","\\mathfrak{L}(\\mathbf{w},b) = \\frac{1}{n} \\sum_{i=1}^n (\\hat{y}_i - y_i)^2 = \\frac{1}{n}\\sum_{i=1}^n (\\text{rn}(\\mathbf{x}_i|\\mathbf{w},b) - y_i)^2.\n","$$"]},{"cell_type":"markdown","metadata":{"id":"O_W-HFqdVevE"},"source":["### <span style=\"color:#4CC9F0\">Función de activación Unidad de Rectificación Lineal (ReLU)</span>\n"]},{"cell_type":"markdown","metadata":{"id":"4-vbnFmsVevE"},"source":["*ReLu* es la función de activación más utilizada actualmente. Implementada principalmente en capas ocultas de la red neuronal. *ReLU* se define como\n","\n","$$\n","f(x) = \\text{ReLU}(x) = \\max(0,x),\n","$$\n","para $x\\in \\mathcal{R}$."]},{"cell_type":"markdown","metadata":{"id":"uKgQo6cRVevE"},"source":["#### <span style=\"color:#4CC9F0\">Ejercicio</span>\n"]},{"cell_type":"markdown","metadata":{"id":"NL2oAvpiVevF"},"source":["Verifique que\n","\n","1. $0\\le f(x)< \\infty$\n","2. $f'(x)= 1$ for $x > 0$, and  $f'(x)= 0$ for $x < 0$.\n","\n","*ReLu* es menos costosa computacionalmente que *Tanh* y *sigmoide* porque involucra operaciones matemáticas más simples.  *ReLu* permite a la red aprender mucho más rápido que la funciones *sigmoide* y *Tanh*. El siguiente fragmento de código dibuja la función de activación *ReLU*."]},{"cell_type":"code","execution_count":14,"metadata":{"id":"lRuDUIsdVevF","colab":{"base_uri":"https://localhost:8080/","height":452},"executionInfo":{"status":"ok","timestamp":1695330131164,"user_tz":300,"elapsed":239,"user":{"displayName":"Camilo Jose Torres Jimenez","userId":"08254179589050810962"}},"outputId":"db37573d-b525-472f-cbea-e8ab7607088c"},"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 640x480 with 1 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\n"},"metadata":{}}],"source":["import numpy as np\n","import matplotlib.pyplot as plt\n","\n","def Relu(x):\n","    y= np.zeros(x.shape)\n","    return np.ndarray.flatten(np.max([[y],[x]], axis =0))\n","\n","x = np.linspace(-5,5,100)\n","plt.title('Gráfico de la función de activación ReLU')\n","plt.plot(x,Relu(x))\n","plt.grid()\n","plt.show()"]},{"cell_type":"markdown","metadata":{"id":"pwKeg_ngVevF"},"source":["## <span style=\"color:#4361EE\">Construcción del modelo Sequential con Keras</span>"]},{"cell_type":"markdown","metadata":{"id":"5gzpEc5kVevF"},"source":["Construyamos nuestro modelo, usando el API Sequential de Keras. Aquí, utilizaremos un modelo `Secuencial` con dos capas ocultas densamente conectadas y una capa de salida que devuelve un único valor continuo. Como función de activación usaremos *ReLU* a la salida de cada capa densa. Podemos definir el modelo, es decir, la red neuronal como sigue:"]},{"cell_type":"code","execution_count":15,"metadata":{"id":"c26juK7ZG8j-","executionInfo":{"status":"ok","timestamp":1695330137744,"user_tz":300,"elapsed":6584,"user":{"displayName":"Camilo Jose Torres Jimenez","userId":"08254179589050810962"}}},"outputs":[],"source":["model = keras.Sequential([\n","layers.Dense(64, activation='relu', input_shape=(normed_train_data.shape[1],)),\n","layers.Dense(64, activation='relu'),\n","layers.Dense(1)\n","])"]},{"cell_type":"markdown","metadata":{"id":"kyUJ5mSIVevG"},"source":["Observe que el modelo es definido dentro de una lista, en donde cada elemento corresponde a una capa de la red."]},{"cell_type":"markdown","metadata":{"id":"E4pHXtsvVevG"},"source":["### <span style=\"color:#4CC9F0\">Compila</span>"]},{"cell_type":"markdown","metadata":{"id":"lk9dqROXVevG"},"source":["Es necesario compilar el modelo para que Tensorflow construya el árbol de cálculo de la red, determine sus parámetros y configure los objetos que usará en el entrenamiento como el optimizador, la función de pérdida y las métricas de evaluación."]},{"cell_type":"code","execution_count":16,"metadata":{"id":"eIIrbWhsVevG","executionInfo":{"status":"ok","timestamp":1695330137746,"user_tz":300,"elapsed":29,"user":{"displayName":"Camilo Jose Torres Jimenez","userId":"08254179589050810962"}}},"outputs":[],"source":["optimizer = tf.keras.optimizers.Adam(0.001)\n","model.compile(loss='mse',\n","                optimizer=optimizer,\n","                metrics=['mae', 'mse'])"]},{"cell_type":"markdown","metadata":{"id":"2pRTpPieVevH"},"source":["### <span style=\"color:#4CC9F0\">Summary</span>"]},{"cell_type":"code","execution_count":17,"metadata":{"id":"FxR1CZk4VevH","colab":{"base_uri":"https://localhost:8080/","height":682},"executionInfo":{"status":"ok","timestamp":1695330138002,"user_tz":300,"elapsed":283,"user":{"displayName":"Camilo Jose Torres Jimenez","userId":"08254179589050810962"}},"outputId":"4e0aad9d-d386-43a3-ea5b-45c547227f0c"},"outputs":[{"output_type":"stream","name":"stdout","text":["Model: \"sequential\"\n","_________________________________________________________________\n"," Layer (type)                Output Shape              Param #   \n","=================================================================\n"," dense (Dense)               (None, 64)                640       \n","                                                                 \n"," dense_1 (Dense)             (None, 64)                4160      \n","                                                                 \n"," dense_2 (Dense)             (None, 1)                 65        \n","                                                                 \n","=================================================================\n","Total params: 4865 (19.00 KB)\n","Trainable params: 4865 (19.00 KB)\n","Non-trainable params: 0 (0.00 Byte)\n","_________________________________________________________________\n"]},{"output_type":"execute_result","data":{"image/png":"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\n","text/plain":["<IPython.core.display.Image object>"]},"metadata":{},"execution_count":17}],"source":["model.summary()\n","plot_model(model, show_shapes=True)"]},{"cell_type":"markdown","metadata":{"id":"0-qWCsh6DlyH"},"source":["## <span style=\"color:#4361EE\">Entrena el modelo</span>"]},{"cell_type":"markdown","metadata":{"id":"l_f6rFfBVevH"},"source":["Entrene el modelo durante 1000 epochs y registre la precisión de entrenamiento y validación en el objeto `history`."]},{"cell_type":"markdown","metadata":{"id":"BNyPuEH6VevH"},"source":["### <span style=\"color:#4CC9F0\">Define un callback para intervenir en la salida</span>"]},{"cell_type":"code","execution_count":18,"metadata":{"id":"sD7qHCmNIOY0","executionInfo":{"status":"ok","timestamp":1695330138198,"user_tz":300,"elapsed":210,"user":{"displayName":"Camilo Jose Torres Jimenez","userId":"08254179589050810962"}}},"outputs":[],"source":["# Muestra el progreso del entrenamiento imprimiendo un solo punto para cada época completada\n","class PrintDot(keras.callbacks.Callback):\n","      def on_epoch_end(self, epoch, logs):\n","        if epoch % 100 == 0: print('')\n","        print('.', end='')\n","\n","epochs = 1000"]},{"cell_type":"markdown","source":["### <span style=\"color:#4CC9F0\">Corre el entrenamiento</span>"],"metadata":{"id":"PEbx-ZLyVevI"}},{"cell_type":"markdown","source":["Se corre el entrenamiento, guardando la historia de la pérdida y de la métricas tanto de entrenamiento como de validación para los análisis de convergencia y comportamiento general del entrenamiento."],"metadata":{"id":"giiZcX5KW3aT"}},{"cell_type":"code","execution_count":19,"metadata":{"id":"DRnm3QqcVevI","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1695330227129,"user_tz":300,"elapsed":88933,"user":{"displayName":"Camilo Jose Torres Jimenez","userId":"08254179589050810962"}},"outputId":"4736d6e7-746a-4532-dffd-5d7c8e87f1d9"},"outputs":[{"output_type":"stream","name":"stdout","text":["\n","....................................................................................................\n","....................................................................................................\n","....................................................................................................\n","....................................................................................................\n","....................................................................................................\n","....................................................................................................\n","....................................................................................................\n","....................................................................................................\n","....................................................................................................\n","...................................................................................................."]}],"source":["history = model.fit(\n","  normed_train_data, train_labels,\n","  epochs=epochs, validation_split = 0.2, verbose=0,\n","  callbacks=[PrintDot()])"]},{"cell_type":"markdown","metadata":{"id":"tQm3pc0FYPQB"},"source":["### <span style=\"color:#4CC9F0\">Visualización del comportamiento del entrenamiento</span>"]},{"cell_type":"markdown","metadata":{"id":"irO8a7uvVevJ"},"source":["Visualice el progreso de entrenamiento del modelo usando las estadísticas almacenadas en el objeto `history`."]},{"cell_type":"code","execution_count":20,"metadata":{"id":"4Xj91b-dymEy","colab":{"base_uri":"https://localhost:8080/","height":206},"executionInfo":{"status":"ok","timestamp":1695330227131,"user_tz":300,"elapsed":28,"user":{"displayName":"Camilo Jose Torres Jimenez","userId":"08254179589050810962"}},"outputId":"4d462ee6-f462-458d-cbe5-fc0ff261b2d5"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["         loss       mae       mse  val_loss   val_mae   val_mse  epoch\n","995  1.941662  0.812403  1.941662  9.489256  2.465098  9.489256    995\n","996  1.997974  0.834159  1.997974  9.234850  2.418804  9.234850    996\n","997  2.008736  0.826191  2.008736  9.158767  2.410529  9.158767    997\n","998  1.972037  0.810211  1.972037  9.289677  2.432204  9.289677    998\n","999  2.072726  0.857649  2.072726  9.728074  2.480057  9.728074    999"],"text/html":["\n","  <div id=\"df-2eab4b8c-e0fd-46df-9321-2e8267f7c917\" class=\"colab-df-container\">\n","    <div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>loss</th>\n","      <th>mae</th>\n","      <th>mse</th>\n","      <th>val_loss</th>\n","      <th>val_mae</th>\n","      <th>val_mse</th>\n","      <th>epoch</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>995</th>\n","      <td>1.941662</td>\n","      <td>0.812403</td>\n","      <td>1.941662</td>\n","      <td>9.489256</td>\n","      <td>2.465098</td>\n","      <td>9.489256</td>\n","      <td>995</td>\n","    </tr>\n","    <tr>\n","      <th>996</th>\n","      <td>1.997974</td>\n","      <td>0.834159</td>\n","      <td>1.997974</td>\n","      <td>9.234850</td>\n","      <td>2.418804</td>\n","      <td>9.234850</td>\n","      <td>996</td>\n","    </tr>\n","    <tr>\n","      <th>997</th>\n","      <td>2.008736</td>\n","      <td>0.826191</td>\n","      <td>2.008736</td>\n","      <td>9.158767</td>\n","      <td>2.410529</td>\n","      <td>9.158767</td>\n","      <td>997</td>\n","    </tr>\n","    <tr>\n","      <th>998</th>\n","      <td>1.972037</td>\n","      <td>0.810211</td>\n","      <td>1.972037</td>\n","      <td>9.289677</td>\n","      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\n"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["<Figure 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\n"},"metadata":{}}],"source":["# función para mostrar pérdida y métricas\n","def plot_history(history):\n","    hist = pd.DataFrame(history.history)\n","    hist['Epoca'] = history.epoch\n","\n","    plt.figure()\n","    plt.xlabel('Epoca')\n","    plt.ylabel(' Error Absoluto Medio [MPG]')\n","    plt.plot(hist['Epoca'], hist['mae'],\n","           label=' Entrenamiento')\n","    plt.plot(hist['Epoca'], hist['val_mae'],\n","           label = 'Validación')\n","    plt.ylim([0,5])\n","    plt.legend()\n","\n","    plt.figure()\n","    plt.xlabel('Epoca')\n","    plt.ylabel('Error Cuadrático Medio [$MPG^2$]')\n","    plt.plot(hist['Epoca'], hist['mse'],\n","           label='Entrenamiento')\n","    plt.plot(hist['Epoca'], hist['val_mse'],\n","           label = 'Validación')\n","    plt.ylim([0,20])\n","    plt.legend()\n","    plt.show()\n","\n","plot_history(history)"]},{"cell_type":"markdown","metadata":{"id":"AqsuANc11FYv"},"source":["Este gráfico muestra poca mejora, o incluso degradación en el error de validación después de aproximadamente 100 épocas. Vamos a actualizar la llamada `model.fit` para detener automáticamente el entrenamiento cuando el puntaje de validación no mejore. Utilizaremos una devolución de llamada(callback)   de *EarlyStopping* que pruebe una condición de entrenamiento para cada época. Si transcurre una cantidad determinada de épocas sin mostrar mejoría, entonces detiene automáticamente el entrenamiento.\n","\n","Puede obtener más información sobre esta devolución de llamada  en este [enlace](https://www.tensorflow.org/versions/master/api_docs/python/tf/keras/callbacks/EarlyStopping)."]},{"cell_type":"code","execution_count":22,"metadata":{"id":"fdMZuhUgzMZ4","colab":{"base_uri":"https://localhost:8080/","height":928},"executionInfo":{"status":"ok","timestamp":1695330230632,"user_tz":300,"elapsed":2743,"user":{"displayName":"Camilo Jose Torres Jimenez","userId":"08254179589050810962"}},"outputId":"8c60d43e-7a1f-4611-b456-6dbeb5db0ae9"},"outputs":[{"output_type":"stream","name":"stdout","text":["\n","..................."]},{"output_type":"display_data","data":{"text/plain":["<Figure size 640x480 with 1 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FfPXVV/jss88wYcIESJKEHTt2YNiwYXjssccAWHaX/P777+jWrZtT8+3atStyc3ORl5eH2NhYAMCuXbsc2vz8889o3749Xn31Vdu4s2fPOrRJTU1FZmYmnnzySaeXmZuba+tVOXr0KAoLC52u29dw1w8REclacHAwRowYgenTpyMvL8923ZHOnTtj48aN+Pnnn5GdnY1nnnnG4eyZhgwYMABJSUlIT0/HL7/8gu3btzsEEusycnJysGLFCpw8eRLvv/8+1qxZ49Bm5syZ+PrrrzFz5kxkZ2cjKysLb7/9dp3LTElJwejRo3HgwAHs2bMHY8aMQb9+/dCrVy/X/jA+gkGFiIhkb+zYsbh27RoGDhxoO6bktddew80334yBAweif//+iImJwfDhw52ep0KhwJo1a1BeXo7evXtj3LhxNQ5WHTp0KF566SVMmjQJN910E37++WfMmDHDoU3//v2xevVqrFu3DjfddBPuvvvuOs88kiQJ3333HcLDw3HnnXdiwIAB6NChA1auXOnaH8SHSEI4eZ6YDOl0Omi1WhQVFSE0NNTb5RARyVZFRQVOnz6NxMREBAQEeLsc8gH1veZc+f5mjwoRERHJFoMKERERyRaDChEREckWgwoRERHJFoMKEZEPacbnT1Az467XGoMKEZEPsF7ptKyszMuVkK+wvtaqX2XXVbwyLRGRD1AqlQgLC7P9XoxGo4EkSV6uiloiIQTKyspQUFCAsLAwKJXKG5ofgwoRkY+IiYkBAJ/9cTtqWmFhYbbX3I1gUCEi8hGSJCE2NhbR0dEwGAzeLodaMJVKdcM9KVYMKkREPkapVLrtS4TI03gwLREREckWgwoRERHJFoMKERERyRaDChEREckWgwoRERHJFoMKERERyRaDChEREckWgwoRERHJFoMKERERyRaDChEREckWgwoRERHJFoMKERERyRaDChEREckWgwoRERHJlmyCyrx58yBJEl588UVvl0JEREQyIYugsnfvXixZsgSpqaneLoWIiIhkxOtBpaSkBKNHj8bHH3+M8PBwb5dDREREMuL1oDJx4kQMGTIEAwYMaLCtXq+HTqdzuBEREVHL5efNha9YsQIHDhzA3r17nWo/d+5czJ4928NVERERkVx4rUclNzcXL7zwAr788ksEBAQ49Zzp06ejqKjIdsvNzfVwlURERORNkhBCeGPBa9euxYMPPgilUmkbZzKZIEkSFAoF9Hq9w7Ta6HQ6aLVaFBUVITQ01NMlExERkRu48v3ttV0/99xzD7KyshzGPfnkk+jSpQumTZvWYEghIiKils9rQSUkJAR/+MMfHMYFBQUhMjKyxngiIiLyTV4/64eIiIioLl4966e6LVu2eLsEIiIikhH2qBAREZFsMagQERGRbDGoEBERkWwxqBAREZFsMagQERGRbDGoEBERkWwxqBAREZFsMagQERGRbDl1wbebb77ZpZlKkoR169ahTZs2jSqKiIiICHAyqBw6dAgvv/wygoODG2wrhMC8efOg1+tvuDgiIiLybU5fQv+VV15BdHS0U23nz5/f6IKIiIiIrJwKKqdPn0ZUVJTTMz169Cji4uIaXRQRERER4GRQad++vUszjY+Pb1QxRERERPZc+vVknU6H0NBQAMC///1vGI1G2zSlUokhQ4a4tzoiIiLyaU4HlfXr12PGjBk4ePAgAGDEiBEoLS21TZckCStXrsSf//xn91dJREREPsnp66h89NFHeP755x3GnThxAmazGWazGXPnzsWyZcvcXiARERH5LqeDSlZWFm677bY6pw8ePBj79u1zS1FEREREgAtBJS8vD2q12ja8efNmh4Nmg4ODUVRU5N7qiIiIyKc5HVQiIiJw4sQJ23CvXr2gUqlsw8ePH0dERIR7qyMiIiKf5nRQufPOO/H+++/XOf3999/HnXfe6ZaiiIiIiAAXgsq0adPw3//+F4888gj27t2LoqIiFBUVYc+ePXj44YexadMmTJs2zZO1EhERkY9x+vTknj17YuXKlRg3bhy+/fZbh2nh4eFYsWKFyz9eSERERFQfSQghXHlCWVkZNmzYgOPHjwMAOnfujHvvvRdBQUEeKbA+Op0OWq0WRUVFtgvRERERkby58v3t0pVphRA4f/48kpKS8MADD8DPz6WnExEREbnE6WNUTp8+jdTUVHTp0gWpqano2LEjr5tCREREHuV0UHnllVdgNBrxxRdf4JtvvkHbtm0xfvx4T9ZGREREPs7pfTc//fQTvvnmG9x+++0AgD/+8Y9o27YtSktLvXJ8ChEREbV8TveoFBQUoHPnzrbh2NhYBAYGoqCgwCOFERERETndoyJJEkpKShAYGGgbp1AoUFxcDJ1OZxvHs2+IiIjIXZwOKkIIJCUl1RjXs2dP22NJkmAymdxbIREREfksp4PK5s2bPVkHERERUQ1OB5V+/fp5sg4iIiKiGpw+mJaIiIioqTndo6JUKp1qx2NUiIiIyF1cOpi2ffv2SE9Ptx1AS0RERORJTgeVPXv2YOnSpXjvvfeQmJiIp556CqNHj0Z4eLgn6yMiIiIf5vQxKr169cLixYuRl5eHKVOmYM2aNWjbti1GjhyJjRs3erJGIiIi8lEuH0wbEBCAxx57DJmZmTh8+DAKCgowaNAgXL161RP1ERERkQ9zetePvXPnziEjIwMZGRkoKyvDK6+8wivSEhERkds5HVQqKyuxZs0aLF26FNu3b8fgwYOxcOFCDB482OkzgoiIiIhc4XRQiY2NRUhICNLT0/HBBx8gOjoaAFBaWurQjj0rRERE5C6SEEI401ChuH44iyRJNaZ747d+dDodtFotioqKGJCIiIiaCVe+v/lbP0RERCRb/K0fIiIiki2nTk/W6XQuzbS4uLhRxRARERHZcyqohIeHo6CgwOmZtmnTBqdOnWp0UURERESAk7t+hBD45JNPEBwc7NRMDQbDDRVFREREBDgZVNq1a4ePP/7Y6ZnGxMRApVI1uigiIiIiwMmgcubMGQ+XQURERFSTy7/1Q0RERNRUGFSIiIhIthhUiIiISLYYVIiIiEi2GFSIiIhItpy+hL69wsJCLF26FNnZ2QCA7t2746mnnoJWq3VrcUREROTbXO5R2bdvHzp27Ih//OMfuHr1Kq5evYoFCxagY8eOOHDggCdqJCIiIh8lCSGEK0+444470KlTJ3z88cfw87N0yBiNRowbNw6nTp3Ctm3bPFJobVz5mWgiIiKSB1e+v10OKoGBgTh48CC6dOniMP7o0aPo1asXysrKXK+4kRhUiIiImh9Xvr9d3vUTGhqKnJycGuNzc3MREhLi6uyIiIiI6uRyUBkxYgTGjh2LlStXIjc3F7m5uVixYgXGjRuHUaNGeaJGIiIi8lEun/Xz7rvvQpIkjBkzBkajEQCgUqkwYcIEzJs3z+0FEhERke9y+RgVq7KyMpw8eRIA0LFjR2g0GrcW5gweo0JERNT8uPL93ajrqACARqNBSkpKY59ORERE1CCngspDDz2EjIwMhIaG4qGHHqq37bfffuv0whcvXozFixfjzJkzACwXjnv99dcxePBgp+dBRERELZdTQUWr1UKSJNtjd2nbti3mzZuHzp07QwiBTz/9FMOGDcPBgwfRvXt3ty2HiIiImqdGH6PiKREREXjnnXcwduzYBtvyGBUiIqLmp0mOUXE3k8mE1atXo7S0FGlpabW20ev10Ov1tmGdTtdU5REREZEXOBVUevbsadv10xBXf+8nKysLaWlpqKioQHBwMNasWYNu3brV2nbu3LmYPXu2S/MnIiKi5supXT/24aCiogIffPABunXrZuv52LVrF44cOYLnnnsOc+fOdamAyspK5OTkoKioCN988w0++eQTbN26tdawUluPSnx8PHf9EBERNSMe/a2fcePGITY2Fm+88YbD+JkzZyI3NxfLli1zvWI7AwYMQMeOHbFkyZIG2/IYFSIioubHo7/1s3r1aowZM6bG+Mceewz/+te/XJ1dDWaz2aHXhIiIiHyXywfTBgYGYseOHejcubPD+B07diAgIMCleU2fPh2DBw9Gu3btUFxcjK+++gpbtmzBhg0bXC2LiIiIWiCXg8qLL76ICRMm4MCBA+jduzcAYPfu3Vi2bBlmzJjh0rwKCgowZswY5OXlQavVIjU1FRs2bMCf/vQnV8siIiKiFqhR11FZtWoV3nvvPWRnZwMAunbtihdeeAGPPvqo2wusD49RISIian48ejCtnDCoEBERNT8ePZgWAAoLC/HJJ5/gf/7nf3D16lUAluunnD9/vjGzIyIiIqqVy8eo/PrrrxgwYAC0Wi3OnDmDcePGISIiAt9++y1ycnLw2WefeaJOIiIi8kEu96hMmTIFTzzxBI4fP+5wls99992Hbdu2ubU4IiIi8m0uB5W9e/fimWeeqTG+TZs2yM/Pd0tRREREREAjgopara71xwB///13REVFuaUoIiIiIqARQWXo0KGYM2cODAYDAECSJOTk5GDatGl4+OGH3V4gERER+S6Xg8r8+fNRUlKC6OholJeXo1+/fujUqRNCQkLw5ptveqJGIiIi8lEun/Wj1WqxceNG/PTTT/j1119RUlKCm2++GQMGDPBEfUREROTDeME3IiIialKufH873aPi7PVRavtlZSIiIqLGcLpHRaFQIDg4GH5+fqjrKZIk2a5U2xTYo0JERNT8eKRHpWvXrrh48SIee+wxPPXUU0hNTb3hQomIiIjq4/RZP0eOHMH333+P8vJy3HnnnejVqxcWL15c6zVViIiIiNzBpdOT+/TpgyVLliAvLw+TJ0/GqlWrEBsbi9GjR0Ov13uqRiIiIvJRjfr15MDAQIwZMwazZ89G7969sWLFCpSVlbm7NiIiIvJxLgeV8+fP46233kLnzp0xcuRI3HrrrThy5AjCw8M9UR8RERH5MKcPpl21ahWWL1+OrVu3YuDAgZg/fz6GDBkCpVLpyfqIiIjIh7l0enK7du0wevRotG7dus52kydPdltxDeHpyURERM2PK9/fTgeVhIQESJJU/8wkCadOnXK+0hvEoEJERNT8eOQ6KmfOnLnRuoiIiIhc0qizfoiIiIiaAoMKERERyRaDChEREckWgwoRERHJFoMKERERyZbTZ/3YM5lMWLt2LbKzswEA3bt3x9ChQ3nxNyIiInIrl4PKiRMnMGTIEJw7dw7JyckAgLlz5yI+Ph7ff/89Onbs6PYiiYiIyDe5vOtn8uTJ6NChA3Jzc3HgwAEcOHAAOTk5SExMbNKr0hIREVHL53KPytatW7Fr1y5ERETYxkVGRmLevHm47bbb3FocERER+TaXe1TUajWKi4trjC8pKYG/v79biiIiIiICGtGjcv/992P8+PFYunQpevfuDQDYvXs3nn32WQwdOtTtBZKPEwIwVQKGcsA/CFCqvF1R45QXApd+AwqOApVlgDqk6hYKBITaDYcA/iGAgifkEREBjQgq77//PtLT05GWlgaVyvKlYTQaMXToUCxcuNDd9ZHcmQxA6SVAX2wJE4ZywFAGGCuuPzZU2I0rs2tXdTOWV2tb7themC3LUvgBER2AVknVbp0tX/ZyYCgHLv8OFGQDF49Y7guyAd051+bjbxdcqgcZtdZx2Dbd7l4TCagCPLOOzYnJCFQUARWFlrBYcc1yX37t+jizCQhpDYTEXr+Fxlr+ls2BocLyHjSUAyEx8nkvOMNsBkrygWtngWtngMKzQMlFQKWp9poPcXxPqEMAdbBlnLJRJ69SM+L0rydXd+LECdvpyV27dkWnTp3cWpgz+OvJHmIyAmWXLR8YJZcs96UF1R5X3cqvertai5BYS2BplXw9vLRKAkLjgAZ+9btRTEbg2mlLD8nFo5b7gmzg6snrwaq60DZAdFcgMBzQl1jCnb6o6r4YqNABZoObCpSAsHaWv0FU8vW/R6tkICjSTctoImZTtbBRaAkatse1jatqr9c1frn+IZYv/lD7ABNnGRdivY9xfy+fEJbaSy5ZAoj9raSg6vFly/uw9HLNdVRrAW0by+tN2wYIbWs33NayDqpA99Zcn4oiSwixDyPW4cIcwKS/sflbQ41/sGNPpTq47qDjH1Tzc6HWr8JaxjnbDgAgWZYjKaoeKxoYtmvf4HOq6jdWWv6ps930Vf8A6i3/BBr1Vf/0VTS+XffhwLBFTm0OZ7ny/e1yUJkzZw6mTp0KjUbjML68vBzvvPMOXn/9ddcrbiTZBRWz2fJFYzJcv7c9NtacZjZaXnQKP0ChrLpXVRv2s3wQ1trGhd0DZhNQdqUqfFR92FkflxQ4ho+yK6j7jVcLSWn5L06lAfwCLPeqAMuHocO4wOu32sbVaBtgNy7QUvPl34FLv1vuL/8OXD5u+Y+sLv7Bdl/SdkEmogPg58QxVUIAuvOOYaTgKHDpWN0fsIHhQHR3SyiJ7gq07g5EdQECwxpenlFvCSx63fUAU/1xhf1wseuBJzDi+t8jyi7YhbW3vMaaihCWcKG7UHU7Z/f4PFB03vK6rNDBpddjbfxDLH//gDDLvf1jSQkU5wPFeVW3fBcCjgQEtao9xNgPq4Or3n9V4aL0UlXQuFRLILnsemBVqCzvEWfr1kReDy7atnYhpirchMQ6H8CMlUBRriW41xZGKgrrf76ktCw7vD0QngAEx1i+IK2v58qSWt4HJTcecMh53YYDj37q1ll6NKgolUrk5eUhOjraYfyVK1cQHR0Nk8nkesWN5LGgcmoLsO3dqqBRWUvQMNpNM14PH3X9J+0xUgNBRmm5VegsPSSu1CcpgKAoICgaCLa7BUUDwa2B4CjLfVC05YvZm8dUlBcCV05cDy/WIHP1FCDqeD1KSiAi0bH3pVWy5cPPFkqqgkldH/4qjSWARHerCiTdLI+DW3umF8dZQli+7C7/Dlw+Zglz1r9NYU7dz1OqgchOdn+PJCAqyTLOP8j1GsqvAUXnrgcP3Xm7x1WBxFDm/DxVmqpwEV4tdIRff1zb9ACt670e+uLr4UWXZxdi7Ifz3dgDVgu11hKCgqIs77egarfg6KrHrSzrKkmWL3Ddecvfvejc9cCnO1d1f965v7mksLyOq/fKBGgt87EPI7oLaDBIBkVZgrA1jIRV3Ye3t8y7MbtvjPqqnkmdXZip51Zp/7i0tpWuNlj9PVzLe7rGqOojhOW9IETV52/VvTDXMg5OtKk+L2H5h8svEPBTV/1TF2C5t95sw+rr7VR27Wu0s2tvbRcQBmgi4E4eDSoKhQIXL15EVFSUw/gff/wRI0aMwKVLl1yvuJE8FlSyvgH+NdY987IGB2uYUKoApf/13hIIS9gxm+xCj92w2eje3QFBrZwLH5qIpv3v2hOMlZYP0svHrve+WINMZc0z1+qk8AMiO1f1kHSrCiRdgbCE5nfQa2WZXag7bhdkjtf/H6o23vGYoFZJli706sHDPpAYK5yrSRNp6X0Irdo9YXtc1SNhDSLO9IA1JbPZ0ktSI8RcsIQYa6Apu2xpLyntgkYrx6ARFO0YSDStPHOMka0Xyz7A2IUYa7B09TNHpbELINXCSFg7S48SkR2PBJXw8HBIkmSbqWSXNk0mE0pKSvDss89i0SL37seqj8eCSmEucG7P9YChVNmFDZUl/VcPH4qqAFJ9mrv+s3YILlVBxhZq7MaZDTXbqEMsAUQTyQPPAMuHdXG+3e4ju91ICuX13Tatq+4jO8vvS9LdzCZL93313WqXj1XtCmykoCjH4OEQRuKa/ngJbzDqLf/BB4Q1j2BrNlt2QemqB5jzluNNQttUhZHE62EkqJV3exGp2fFIUPn0008hhMBTTz2FhQsXQqvV2qb5+/sjISEBaWlpN1a5i2R3jApRS1R6BbhyvNqutWOWA/EcQkicpRvf+jgklmceEVGtXPn+dvrf6/T0dABAYmIi+vbtazs1mYhauKBIy63dH71dCRH5IJf3AyQmJiIvL6/O6e3atbuhgoiIiIisXA4qCQkJDsenVNeUZ/0QERFRy+ZyUDl48KDDsMFgwMGDB7FgwQK8+eabbiuMiIiIyOWg0qNHjxrjevXqhbi4OLzzzjt46KGH3FIYERERkdvOlUtOTsbevXvdNTsiIiIi13tUdDrHq3QKIZCXl4dZs2ahc+fObiuMiIiIyOWgEhYWVuNgWiEE4uPjsWLFCrcVRkRERORyUNm8ebPDsEKhQFRUFDp16gQ/P171lIiIiNzH5WTRr18/T9RBREREVINTQWXdunVOz3Do0KGNLoaIiIjInlNBZfjw4U7NTJIkXvCNiIiI3MapoGI2mz1dBxEREVENzeA3x4mIiMhXNSqobN26FQ888AA6deqETp06YejQodi+fbu7ayMiIiIf53JQ+eKLLzBgwABoNBpMnjwZkydPRmBgIO655x589dVXnqiRiIiIfJQkhBCuPKFr164YP348XnrpJYfxCxYswMcff4zs7Gy3FlgfnU4HrVaLoqIihIaGNtlyiYiIqPFc+f52uUfl1KlTeOCBB2qMHzp0KE6fPu3q7IiIiIjq5HJQiY+PR2ZmZo3xmzZtQnx8vFuKIiIiIgIacWXal19+GZMnT8ahQ4fQt29fAMCOHTuQkZGB9957z+0FEhERke9yOahMmDABMTExmD9/PlatWgXActzKypUrMWzYMLcXSERERL7L5YNp5YQH0xIRETU/Hj2YNjc3F+fOnbMN79mzBy+++CI++ugj1yslIiIiqofLQeUvf/kLNm/eDADIz8/HgAEDsGfPHrz66quYM2eO2wskIiIi3+VyUDl8+DB69+4NAFi1ahVSUlLw888/48svv0RGRoZL85o7dy5uvfVWhISEIDo6GsOHD8exY8dcLYmIiIhaKJeDisFggFqtBmA5JXno0KEAgC5duiAvL8+leW3duhUTJ07Erl27sHHjRhgMBtx7770oLS11tSwiIiJqgVw+66d79+748MMPMWTIEGzcuBFvvPEGAODChQuIjIx0aV4//PCDw3BGRgaio6Oxf/9+3Hnnna6WRkRERC2Myz0qb7/9NpYsWYL+/ftj1KhR6NGjBwBg3bp1tl1CjVVUVAQAiIiIqHW6Xq+HTqdzuBEREVHL1ajTk00mE3Q6HcLDw23jzpw5A41Gg+jo6EYVYjabMXToUBQWFuKnn36qtc2sWbMwe/bsGuN5ejIREVHz4crpyY2+jkpBQYHtwNfk5ORGBxSrCRMm4D//+Q9++ukntG3bttY2er0eer3eNqzT6RAfH8+gQkRE1Iy4ElRcPkaluLgYzz33HFasWAGTyQQAUCqVGDFiBBYtWgStVutywZMmTcL69euxbdu2OkMKAKjVatuBvERERNTyuXyMyrhx47B7926sX78ehYWFKCwsxPr167Fv3z4888wzLs1LCIFJkyZhzZo1+PHHH5GYmOhqOURERNSCubzrJygoCBs2bMDtt9/uMH779u0YNGiQS6cWP/fcc/jqq6/w3XffITk52TZeq9UiMDCwwefzEvpERETNj0cvoR8ZGVnr7h2tVutwcK0zFi9ejKKiIvTv3x+xsbG228qVK10ti4iIiFogl49Ree211zBlyhR8/vnniImJAWC5lP4rr7yCGTNmuDSvZvx7iERERNQEnAoqPXv2hCRJtuHjx4+jXbt2aNeuHQAgJycHarUaly5dcvk4FSIiIqK6OBVUhg8f7uEyiIiIiGpq9HVUamMymaBUKt01uwbxYFoiIqLmx6MH09bm999/x7Rp0+q9BgoRERGRqxodVMrKyrB8+XLccccd6NatG7Zu3YopU6a4szYiIiLycS6f9bNr1y588sknWL16Ndq1a4fs7Gxs3rwZd9xxhyfqIyIiIh/mdI/K/Pnz0b17d/z5z39GeHg4tm3bhqysLEiShMjISE/WSERERD7K6R6VadOmYdq0aZgzZ06THjBLREREvsvpHpU33ngDq1evRmJiIqZNm4bDhw97si4iIiIi54PK9OnT8fvvv+Pzzz9Hfn4++vTpgx49ekAIgWvXrnmyRiIiIvJRLp/1069fP3z66afIz8/Hc889h1tuuQX9+vVD3759sWDBAk/USERERD7KLRd8y8rKwtKlS/HVV1+hoKDAHXU5hRd8IyIian5c+f5265VpDQYDVCqVu2bXIAYVIiKi5qfJr0xr1ZQhhYiIiFo+twYVIiIiIndiUCEiIiLZcimoGI1GfPbZZ7h48aKn6iEiIiKycSmo+Pn54dlnn0VFRYWn6iEiIiKycXnXT+/evXHo0CEPlEJERETkyOVfT37uuecwZcoU5Obm4pZbbkFQUJDD9NTUVLcVR0RERL7N5euoKBQ1O2EkSYIQApIkwWQyua24hvA6KkRERM2PK9/fLveonD59utGFEREREbnC5aDSvn17T9RBREREVIPLQQUATp48iYULFyI7OxsA0K1bN7zwwgvo2LGjW4sjIiIi3+byWT8bNmxAt27dsGfPHqSmpiI1NRW7d+9G9+7dsXHjRk/USERERD7K5YNpe/bsiYEDB2LevHkO4//2t7/hv//9Lw4cOODWAuvDg2mJiIiaH4/+KGF2djbGjh1bY/xTTz2Fo0ePujo7IiIiojq5HFSioqJqveDboUOHEB0d7Y6aiIiIiAA04mDap59+GuPHj8epU6fQt29fAMCOHTvw9ttvY8qUKW4vkIiIiHyXy8eoCCGwcOFCzJ8/HxcuXAAAxMXF4ZVXXsHkyZMhSZJHCq0Nj1EhIiJqfjx2wTej0YivvvoKf/nLX/DSSy+huLgYABASEtL4aomIiIjqcEO/nhwSEsKQQkRERB7TqF9PPnjwoCdqISIiInLQqF9Pfvnll3Hu3Dn+ejIRERF5FH89mYiIiJoUfz2ZiIiIWgSXgorBYMDdd9+N9evXo2vXrp6qiYiIiAiAiwfTqlQq2xk/RERERJ7m8lk/EydOxNtvvw2j0eiJeoiIiIhsXD5GZe/evcjMzMR///tfpKSk1Djr59tvv3VbcUREROTbXA4qYWFhePjhhz1RCxEREZEDl4PK8uXLPVEHERERUQ1OH6NSUFBQ73Sj0Yg9e/bccEFEREREVk4HldjYWIewkpKSgtzcXNvwlStXkJaW5t7qiIiIyKc5HVSqX8D2zJkzMBgM9bYhIiIiuhEun55cH0mS3Dk7IiIi8nFuDSpERERE7uT0WT+SJKG4uBgBAQG2HyAsKSmBTqcDANs9ERERkbs4HVSEEEhKSnIY7tmzp8Mwd/0QERGROzkdVDZv3uzJOoiIiIhqcDqo9OvXz5N1EBEREdXAg2mJiIhIthhUiIiISLYYVIiIiEi2GFSIiIhIthhUiIiISLYYVIiIiEi2GFSIiIhIthhUiIiISLYYVIiIiEi2GFSIiIhIthhUiIiISLYYVIiIiEi2vBpUtm3bhgceeABxcXGQJAlr1671ZjlEREQkM14NKqWlpejRowcWLVrkzTKIiIhIpvy8ufDBgwdj8ODB3iyBiIiIZMyrQcVVer0eer3eNqzT6bxYDREREXlaszqYdu7cudBqtbZbfHy8t0siIiIiD2pWQWX69OkoKiqy3XJzc71dEhEREXlQs9r1o1aroVarvV0GERERNZFm1aNCREREvsWrPSolJSU4ceKEbfj06dM4dOgQIiIi0K5dOy9WRkRERHLg1aCyb98+3HXXXbbhKVOmAADS09ORkZHhpapuXKXRjKullbhcosflEj2ulFgeX6kaZx2+VlqJNuGBuDUhArcmRODm9uHQBqq8XT4REZFsSEII4e0iGkun00Gr1aKoqAihoaEeW44QAroKI65Yw0axHpdLKy3DJXbho1SPy8V66CqMjVqOJAHJrUPQOzECvRIi0DshAjHaADevDRERkXe58v3drA6mbSo/Hb+MT346ZQsgV0oqUWkyuzQPpUJCZJA/WgWrERlcdR/kj1Yhatt4rUaFExdLsOfMVew7cxVnrpTht/xi/JZfjM92ngUAxEcE4tb2Ebg1MQK3JoSjY1QwJEnyxGoTERHJDoNKLQrLK7Hl2KUa40PUfogM9kdksBqtrPdB1mFrILGEkNAAFRSKhgPFze3C8eitluvBFOgqsO/sNew5fRX7zl7F0Qs65F4tR+7V8/j24HkAQLhGZett6ZUQjj+00UKl5DHRcmYwmfH7xWJknStC1vkilBtMiA4JQHSIGtGhaofHGn++JYmI7HHXTy3OF5Zjx4nLttARWdUbEqBSum0ZziiuMOBgTiH2nrmKvWeu4mBOIfRGx56dAJUCPePDbT0uN7cLR5DavV92JrNASYURugqD5VZuRHGFAbqKqvtyIypNJpjMgMlshskMmIWAySxgEgImk+XeXDVsNFc9NguYq4atj01mAbMZMJrNMAnY2pnMAhFB/khqHYzOrUOQ1DoESa2DEabxd+u63iijyYwTl0psoeTXc0U4mqdDpdG5HrlgtR+iQ9SIqrpFhwRUhRnHx9pAFXvWqEUxmwV0FQYUVxihVikQ5O+HQJXSqX/4qPlx5fubQaUZqTSacfhCEfaevoq9Z65h39mrKCwzOLRRKiR0iw2tOkA3HL0SIhAS4Gf7ANCVOwaM4qrwYZ1WbA0kdmGkRN+4Y26aQnSIGkmtQ9C5dTCSW4egc9Xj0ADPH5RsMgucvlyCX89ZAknW+SIcuVCECkPNUBIS4IfUtlqktAmDNlCFguIKFBTrcUmntz0uqzQ5vWx/PwWigtWOIcauhyY0UAV/pQJ+SgkqpQKqqns/pQSVQgGVnwJ+Cgn+SoWsvgiEXXA1mS0fTdb6GcyaDyEEyg0mXCmpxLWySlwttd4bcLVUj6ulBlwrrcTVskrLfdV0cy3fRoEqJYLUSgT6Ky3hpepe46+03NR+0Kiq7v2VCPJXQmOdrr7eLshuXKBKCaWMXve+iEHFR5jNAicvWY9xsewyOl9Y7rHlBagUCAlQITTAD6GBKtvjkAAV1H4KKBUS/BQSFAoJSsly76eQoFRIUEgSlApAqVBAKVkClXW6ZZrdTbo+D6WyaliSkK+rwO8Xi/H7xWIcv1hS77rGagNsvS7WHpjO0cGN7m0ymwXOXCm19ZJknbOEktJawkWw2g9/aBOKlDZapLQNQ2obLdpHahr8oi3RG1Ggs4SWgmI9CnQVuGR9XFyBAp3lcVG5od75uEohWcOAJRD4KRVQKSRbmKkxrSr0KCTJ1jtmNJtt4cJkdgwb1YeN1p40k/l6r1vV+Po+jVRK+1oUUPspHMf5KeBvN+zvp4C/Xb0qu2F/P8f5hAaoEBpoeS2HVL2mra9tfz/uWq0wmFBUbrCFjqul1oDhOO56IKms0fvrLLWfotHPdYUlAPkhWG25tzz2uz7O3w/BAdfH2Y93bOuHAJWCQdpFDCo+7EJhOfZWBZe9Z67i2MViCGE5oyhY7Vf1gWz5MA61Cx3WD2Xrh3Vo1Qe2/TS5fWCX6I04XhVcfr9YYgsw+bqKOp/TNjzQoQcmqXUIOkUHO+zWE0Ig52oZfj1XhMNVweTw+SIU19KzpPFXontcKFLahFl6TNpqkRgZ5NFeigqDyRZgLlX1xhTY9cwU6PQo1htgNAkYTAIGkxlGkxkGk3D5oHCyfHFa3zO2oG4LNPaPVXbtrO8vFYID/GTz37vBZEZhmQFF5ZW4VmZAYZklaBRV3ReWG1BYVolrpQbb48IyA8oNzvf22fP3UyBC44+IIMstPMgfERoVIoLUiAhSVQ1bxkcG+SNM4w9/PwXMZoEKowlllSaU6U0oMxhRqjehrNJoGWe915tsw6X24wwmlOmNdtNMKK80obTSWG8YbiylQoLGX1kj1Gjse36qHgf6Kx16gDT+SgSq/BCkrnrsb+0hUsJf2XIDEIMK2ZTojTALgWB/P1l18XtSUZkBxwuuhxdrkLlcoq+1vSQB7SI06BwdggqDCVnni2rttVD7KdA9LhSpbcOQ0kaL1LZadIgKls2XkDOEXe9FpclcFWbMVWHG+rgq3JjNqDRaekscxlcFHiEE/BQKW0+Yn8KxF81PoYBCgRptamurtHuOfVshAIPZDIPx+vL1RrOtZoPJUuP1x2ZU2tXqMM6+nd20CoPZ4Zgr627Q2nrLGitQpbT14vhX69Gx9fz4SVXTr/f+VB9f83nXe5AAoMgaNMocg4Y1jNQWtp2lkIAwa+jQ+CM8yC5waK4Hkcggf9uwxl8pqy9aIQT0RjNK9EaU6U0o0VsCToneiFK9ESUV1scmh/GlervxervxbnyN1EapkGyhRVN1zI7D7i7/668rP6VU1WNo7WG0DPtV9Y7aXls12kq215t1V3H1aWo/BdR+7j1Gk0GFqBbXSisdgov18bWymqHEX6lA17hQpLax9JKktNGic3Qw/HiGlc+ofhB5cYXR7liuqmF9tWO77MJOcYWh1uOV5EAbqEKYRoUwjT/CAlUItz7WWEKH4zR/aDUqhKh9558dZ5nNAmUGx/BiDTQlegPKqnpyyipNDj1B5dV6esoqjVU9PpZhufV8DkmNxaK/3OzWefI6KkS1CA/yR58OkejTIdI2TgiByyWVOH6xGMcLSuDvp0BKGy2SWofIblcXNS2lQoJWo4JW0/gDsyuNlt6aUr3J1otTveen0q6HyNZbZLy+q8463XZf7TnW5wGWAFIjaASpoA30R3hVCAkNVDWrXkA5UygkBFcdp9LajfM1msxVu6/swk1VILIFH4MJ5ZXGGq8h+95E62vIUDXdaLZvK2p9TmXVa8/Sk2rpx/D38j9oDCrk0yRJsp0K3LdTK2+XQy2Mv5/CcnmDYG9XQs2Jn1KBUKWiSc5erI8QluPcBLy744VBhYiIiGqQJAn+ft7vfWPfNhEREckWgwoRERHJFoMKERERyRaDChEREckWgwoRERHJFoMKERERyRaDChEREckWgwoRERHJFoMKERERyRaDChEREckWgwoRERHJFoMKERERyRaDChEREckWgwoRERHJFoMKERERyRaDChEREckWgwoRERHJFoMKERERyRaDChEREckWgwoRERHJFoMKERERyRaDChEREckWgwoRERHJFoMKERERyRaDChEREckWgwoRERHJFoMKERERyRaDChEREckWgwoRERHJFoMKERERyRaDChEREckWgwoRERHJFoMKERERyRaDChEREckWgwoRERHJFoMKERERyRaDChEREckWgwoRERHJFoMKERERyRaDChEREckWgwoRERHJFoMKERERyRaDChEREckWgwoRERHJFoMKERERyRaDChEREckWgwoRERHJFoMKERERyRaDChEREckWgwoRERHJFoMKERERyRaDChEREcmWLILKokWLkJCQgICAAPTp0wd79uzxdklEREQkA14PKitXrsSUKVMwc+ZMHDhwAD169MDAgQNRUFDg7dKIiIjIy7weVBYsWICnn34aTz75JLp164YPP/wQGo0Gy5Yt83ZpRERE5GV+3lx4ZWUl9u/fj+nTp9vGKRQKDBgwADt37qzRXq/XQ6/X24aLiooAADqdzvPFEhERkVtYv7eFEA229WpQuXz5MkwmE1q3bu0wvnXr1vjtt99qtJ87dy5mz55dY3x8fLzHaiQiIiLPKC4uhlarrbeNV4OKq6ZPn44pU6bYhs1mM65evYrIyEhIkuTWZel0OsTHxyM3NxehoaFunbec+ep6A1x3X1x3X11vwHfX3VfXG5DXugshUFxcjLi4uAbbejWotGrVCkqlEhcvXnQYf/HiRcTExNRor1aroVarHcaFhYV5skSEhoZ6fYN6g6+uN8B198V199X1Bnx33X11vQH5rHtDPSlWXj2Y1t/fH7fccgsyMzNt48xmMzIzM5GWlubFyoiIiEgOvL7rZ8qUKUhPT0evXr3Qu3dvLFy4EKWlpXjyySe9XRoRERF5mdeDyogRI3Dp0iW8/vrryM/Px0033YQffvihxgG2TU2tVmPmzJk1djW1dL663gDX3RfX3VfXG/DddffV9Qaa77pLwplzg4iIiIi8wOsXfCMiIiKqC4MKERERyRaDChEREckWgwoRERHJlk8HlUWLFiEhIQEBAQHo06cP9uzZU2/71atXo0uXLggICEBKSgr+/e9/N1Gl7jF37lzceuutCAkJQXR0NIYPH45jx47V+5yMjAxIkuRwCwgIaKKK3WfWrFk11qNLly71Pqe5b2+rhISEGusuSRImTpxYa/vmus23bduGBx54AHFxcZAkCWvXrnWYLoTA66+/jtjYWAQGBmLAgAE4fvx4g/N19XPCG+pbd4PBgGnTpiElJQVBQUGIi4vDmDFjcOHChXrn2Zj3jDc0tN2feOKJGusxaNCgBucr9+3e0HrX9p6XJAnvvPNOnfOU6zb32aCycuVKTJkyBTNnzsSBAwfQo0cPDBw4EAUFBbW2//nnnzFq1CiMHTsWBw8exPDhwzF8+HAcPny4iStvvK1bt2LixInYtWsXNm7cCIPBgHvvvRelpaX1Pi80NBR5eXm229mzZ5uoYvfq3r27w3r89NNPdbZtCdvbau/evQ7rvXHjRgDAI488UudzmuM2Ly0tRY8ePbBo0aJap//973/H+++/jw8//BC7d+9GUFAQBg4ciIqKijrn6ernhLfUt+5lZWU4cOAAZsyYgQMHDuDbb7/FsWPHMHTo0Abn68p7xlsa2u4AMGjQIIf1+Prrr+udZ3PY7g2tt/365uXlYdmyZZAkCQ8//HC985XlNhc+qnfv3mLixIm2YZPJJOLi4sTcuXNrbf/oo4+KIUOGOIzr06ePeOaZZzxapycVFBQIAGLr1q11tlm+fLnQarVNV5SHzJw5U/To0cPp9i1xe1u98MILomPHjsJsNtc6vSVscwBizZo1tmGz2SxiYmLEO++8YxtXWFgo1Gq1+Prrr+ucj6ufE3JQfd1rs2fPHgFAnD17ts42rr5n5KC2dU9PTxfDhg1zaT7Nbbs7s82HDRsm7r777nrbyHWb+2SPSmVlJfbv348BAwbYxikUCgwYMAA7d+6s9Tk7d+50aA8AAwcOrLN9c1BUVAQAiIiIqLddSUkJ2rdvj/j4eAwbNgxHjhxpivLc7vjx44iLi0OHDh0wevRo5OTk1Nm2JW5vwPLa/+KLL/DUU0/V+0OeLWWbW50+fRr5+fkO21Sr1aJPnz51btPGfE40F0VFRZAkqcHfSnPlPSNnW7ZsQXR0NJKTkzFhwgRcuXKlzrYtcbtfvHgR33//PcaOHdtgWzluc58MKpcvX4bJZKpx9dvWrVsjPz+/1ufk5+e71F7uzGYzXnzxRdx22234wx/+UGe75ORkLFu2DN999x2++OILmM1m9O3bF+fOnWvCam9cnz59kJGRgR9++AGLFy/G6dOncccdd6C4uLjW9i1te1utXbsWhYWFeOKJJ+ps01K2uT3rdnNlmzbmc6I5qKiowLRp0zBq1Kh6f5jO1feMXA0aNAifffYZMjMz8fbbb2Pr1q0YPHgwTCZTre1b4nb/9NNPERISgoceeqjednLd5l6/hD55x8SJE3H48OEG9z+mpaU5/EBk37590bVrVyxZsgRvvPGGp8t0m8GDB9sep6amok+fPmjfvj1WrVrl1H8ZLcXSpUsxePDgen9avaVsc6rJYDDg0UcfhRACixcvrrdtS3nPjBw50vY4JSUFqamp6NixI7Zs2YJ77rnHi5U1nWXLlmH06NENHhQv123ukz0qrVq1glKpxMWLFx3GX7x4ETExMbU+JyYmxqX2cjZp0iSsX78emzdvRtu2bV16rkqlQs+ePXHixAkPVdc0wsLCkJSUVOd6tKTtbXX27Fls2rQJ48aNc+l5LWGbW7ebK9u0MZ8TcmYNKWfPnsXGjRvr7U2pTUPvmeaiQ4cOaNWqVZ3r0dK2+/bt23Hs2DGX3/eAfLa5TwYVf39/3HLLLcjMzLSNM5vNyMzMdPhP0l5aWppDewDYuHFjne3lSAiBSZMmYc2aNfjxxx+RmJjo8jxMJhOysrIQGxvrgQqbTklJCU6ePFnnerSE7V3d8uXLER0djSFDhrj0vJawzRMTExETE+OwTXU6HXbv3l3nNm3M54RcWUPK8ePHsWnTJkRGRro8j4beM83FuXPncOXKlTrXoyVtd8DSi3rLLbegR48eLj9XNtvc20fzesuKFSuEWq0WGRkZ4ujRo2L8+PEiLCxM5OfnCyGEePzxx8Xf/vY3W/sdO3YIPz8/8e6774rs7Gwxc+ZMoVKpRFZWlrdWwWUTJkwQWq1WbNmyReTl5dluZWVltjbV13v27Nliw4YN4uTJk2L//v1i5MiRIiAgQBw5csQbq9BoL7/8stiyZYs4ffq02LFjhxgwYIBo1aqVKCgoEEK0zO1tz2QyiXbt2olp06bVmNZStnlxcbE4ePCgOHjwoAAgFixYIA4ePGg7s2XevHkiLCxMfPfdd+LXX38Vw4YNE4mJiaK8vNw2j7vvvlv885//tA039DkhF/Wte2VlpRg6dKho27atOHTokMN7X6/X2+ZRfd0bes/IRX3rXlxcLKZOnSp27twpTp8+LTZt2iRuvvlm0blzZ1FRUWGbR3Pc7g293oUQoqioSGg0GrF48eJa59FctrnPBhUhhPjnP/8p2rVrJ/z9/UXv3r3Frl27bNP69esn0tPTHdqvWrVKJCUlCX9/f9G9e3fx/fffN3HFNwZArbfly5fb2lRf7xdffNH2N2rdurW47777xIEDB5q++Bs0YsQIERsbK/z9/UWbNm3EiBEjxIkTJ2zTW+L2trdhwwYBQBw7dqzGtJayzTdv3lzr69u6bmazWcyYMUO0bt1aqNVqcc8999T4e7Rv317MnDnTYVx9nxNyUd+6nz59us73/ubNm23zqL7uDb1n5KK+dS8rKxP33nuviIqKEiqVSrRv3148/fTTNQJHc9zuDb3ehRBiyZIlIjAwUBQWFtY6j+ayzSUhhPBolw0RERFRI/nkMSpERETUPDCoEBERkWwxqBAREZFsMagQERGRbDGoEBERkWwxqBAREZFsMagQERGRbDGoEBERkWwxqBCR2zzxxBOQJKnGbdCgQd4ujYiaKT9vF0BELcugQYOwfPlyh3FqtdpL1RBRc8ceFSJyK7VajZiYGIdbeHg4AECSJCxevBiDBw9GYGAgOnTogG+++cbh+VlZWbj77rsRGBiIyMhIjB8/HiUlJQ5tli1bhu7du0OtViM2NhaTJk2yTVuwYAFSUlIQFBSE+Ph4PPfcczWeT0TNB4MKETWpGTNm4OGHH8Yvv/yC0aNHY+TIkcjOzgYAlJaWYuDAgQgPD8fevXuxevVqbNq0ySGILF68GBMnTsT48eORlZWFdevWoVOnTrbpCoUC77//Po4cOYJPP/0UP/74I/761782+XoSkZt4+1cRiajlSE9PF0qlUgQFBTnc3nzzTSGE5Re8n332WYfn9OnTR0yYMEEIIcRHH30kwsPDRUlJiW36999/LxQKhe0Xb+Pi4sSrr77qdE2rV68WkZGRN7pqROQlPEaFiNzqrrvuwuLFix3GRURE2B6npaU5TEtLS8OhQ4cAANnZ2ejRoweCgoJs02+77TaYzWYcO3YMkiThwoULuOeee+pc/qZNmzB37lz89ttv0Ol0MBqNqKioQFlZGTQajRvWkIiaEnf9EJFbBQUFoVOnTg43+6ByIwIDA+udfubMGdx///1ITU3Fv/71L+zfvx+LFi0CAFRWVrqlBiJqWgwqRNSkdu3aVWO4a9euAICuXbvil19+QWlpqW36jh07oFAokJycjJCQECQkJCAzM7PWee/fvx9msxnz58/HH//4RyQlJeHChQueWxki8jju+iEit9Lr9cjPz3cY5+fnh1atWgEAVq9ejV69euH222/Hl19+iT179mDp0qUAgNGjR2PmzJlIT0/HrFmzcOnSJTz//PN4/PHH0bp1awDArFmz8OyzzyI6OhqDBw9GcXExduzYgeeffx6dOnWCwWDAP//5TzzwwAPYsWMHPvzww6b9AxCRe3n7IBkiajnS09MFgBq35ORkIYTlYNpFixaJP/3pT0KtVouEhASxcuVKh3n8+uuv4q677hIBAQEiIiJCPP3006K4uNihzYcffiiSk5OFSqUSsbGx4vnnn7dNW7BggYiNjRWBgYFi4MCB4rPPPhMAxLVr1zy+/kTkfpIQQngxJxGRD5EkCWvWrMHw4cO9XQoRNRM8RoWIiIhki0GFiIiIZIsH0xJRk+GeZiJyFXtUiIiISLYYVIiIiEi2GFSIiIhIthhUiIiISLYYVIiIiEi2GFSIiIhIthhUiIiISLYYVIiIiEi2GFSIiIhItv4foS0qmFpjD8IAAAAASUVORK5CYII=\n"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["<Figure 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\n"},"metadata":{}}],"source":["# El parámetro de paciencia (patience) es la cantidad de épocas para verificar la mejora.\n","early_stop = keras.callbacks.EarlyStopping(monitor='val_loss', patience=10)\n","\n","history = model.fit(normed_train_data, train_labels, epochs=epochs,\n","                    validation_split = 0.2, verbose=0, callbacks=[early_stop, PrintDot()])\n","\n","plot_history(history)"]},{"cell_type":"markdown","metadata":{"id":"3St8-DmrX8P4"},"source":["El gráfico muestra que en el conjunto de validación, el error promedio generalmente es de alrededor de +/- 2 MPG. ¿Es esto bueno? Le dejaremos esa decisión a usted.\n","\n","Veamos qué tan bien generaliza el modelo al usar el conjunto **test**, el cual no usamos al entrenar el modelo. Esto nos dice qué tan bien podemos esperar que el modelo prediga cuándo lo usamos en el mundo real."]},{"cell_type":"code","execution_count":23,"metadata":{"id":"jl_yNr5n1kms","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1695330230981,"user_tz":300,"elapsed":355,"user":{"displayName":"Camilo Jose Torres Jimenez","userId":"08254179589050810962"}},"outputId":"8f704eec-18cf-47d8-9efa-f0ae19528e02"},"outputs":[{"output_type":"stream","name":"stdout","text":["3/3 - 0s - loss: 6.2925 - mae: 1.9252 - mse: 6.2925 - 30ms/epoch - 10ms/step\n","Error Absoluto Medio (conjunto de prueba):  1.93 MPG\n"]}],"source":["loss, mae, mse = model.evaluate(normed_test_data, test_labels, verbose=2)\n","\n","print(\"Error Absoluto Medio (conjunto de prueba): {:5.2f} MPG\".format(mae))"]},{"cell_type":"markdown","metadata":{"id":"BYMIe9V7VevK"},"source":["## <span style=\"color:#4361EE\">Predicciones</span>\n"]},{"cell_type":"markdown","metadata":{"id":"ft603OzXuEZC"},"source":["Finalmente, prediga los valores de MPG utilizando datos en el conjunto de prueba:"]},{"cell_type":"code","execution_count":24,"metadata":{"id":"Xe7RXH3N3CWU","colab":{"base_uri":"https://localhost:8080/","height":466},"executionInfo":{"status":"ok","timestamp":1695330231235,"user_tz":300,"elapsed":269,"user":{"displayName":"Camilo Jose Torres Jimenez","userId":"08254179589050810962"}},"outputId":"777795f5-f5cc-4696-e497-6948b2f161a0"},"outputs":[{"output_type":"stream","name":"stdout","text":["3/3 [==============================] - 0s 4ms/step\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 640x480 with 1 Axes>"],"image/png":"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\n"},"metadata":{}}],"source":["test_predictions = model.predict(normed_test_data).flatten()\n","\n","plt.scatter(test_labels, test_predictions)\n","plt.xlabel('Valores verdaderos [MPG]')\n","plt.ylabel('Predicciones [MPG]')\n","plt.axis('equal')\n","plt.axis('square')\n","plt.xlim([0,plt.xlim()[1]])\n","plt.ylim([0,plt.ylim()[1]])\n","_ = plt.plot([-100, 100], [-100, 100])"]},{"cell_type":"markdown","metadata":{"id":"19wyogbOSU5t"},"source":["Parece que nuestro modelo predice razonablemente bien. Demos un vistazo a la distribución de errores."]},{"cell_type":"code","execution_count":25,"metadata":{"id":"f-OHX4DiXd8x","colab":{"base_uri":"https://localhost:8080/","height":450},"executionInfo":{"status":"ok","timestamp":1695330231584,"user_tz":300,"elapsed":365,"user":{"displayName":"Camilo Jose Torres Jimenez","userId":"08254179589050810962"}},"outputId":"ef8fdd6c-8d98-4a5b-e4be-ffb85a96bfb9"},"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 640x480 with 1 Axes>"],"image/png":"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\n"},"metadata":{}}],"source":["error = test_predictions - test_labels\n","plt.hist(error, bins = 25)\n","plt.xlabel(\"Error de predicción [MPG]\")\n","_ = plt.ylabel(\"Conteo\")"]},{"cell_type":"markdown","metadata":{"id":"m0CB5tBjSU5w"},"source":["No es del todo gaussiano, pero podríamos esperar eso porque el número de muestras es muy pequeño."]},{"cell_type":"markdown","metadata":{"id":"vgGQuV-yqYZH"},"source":["## <span style=\"color:#4361EE\">Conclusión</span>"]},{"cell_type":"markdown","metadata":{"id":"0NF8m0dUVevL"},"source":["\n","Este cuaderno introdujo algunas técnicas para manejar un problema de regresión.\n","\n","* El error cuadrático medio (MSE) es una función de pérdida común utilizada para problemas de regresión (se utilizan diferentes funciones de pérdida para problemas de clasificación).\n","* Del mismo modo, las métricas de evaluación utilizadas para la regresión difieren de la clasificación. Una métrica de regresión común es el error absoluto medio (MAE).\n","* Cuando las características de datos de entrada numéricos tienen valores con diferentes rangos, cada característica debe escalarse independientemente al mismo rango.\n","* Si no hay muchos datos de entrenamiento, una técnica es preferir una red pequeña con pocas capas ocultas para evitar el sobreajuste.\n","* La detención temprana es una técnica útil para evitar el sobreajuste."]}],"metadata":{"colab":{"provenance":[],"gpuType":"T4"},"kernelspec":{"display_name":"Python 3","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.10.12"},"vscode":{"interpreter":{"hash":"3620b340ed2ed479d71e72c732c6d6a6eac39d8adbece51414abdea5ed84aec5"}},"accelerator":"GPU"},"nbformat":4,"nbformat_minor":0}