tu-primera-red-neuronal-con-keras.ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"kernelspec":{"display_name":"Python 3","language":"python","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":"3.7.7"},"colab":{"name":"Mi primera red con Keras.ipynb","provenance":[],"collapsed_sections":[]},"accelerator":"GPU"},"cells":[{"cell_type":"markdown","metadata":{"id":"vxnLo_oW3nls"},"source":["## Importando librerías"]},{"cell_type":"code","metadata":{"id":"vQIbRdmt3nl0"},"source":["from keras.datasets import mnist\n","from keras import layers, models\n","from keras.utils import to_categorical\n","import numpy as np\n","import matplotlib.pyplot as plt"],"execution_count":null,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"TEL0A9SR3nl2"},"source":["## Nuestro set de datos"]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"wM6zjAbn3nl2","executionInfo":{"status":"ok","timestamp":1615929010417,"user_tz":300,"elapsed":2339,"user":{"displayName":"Carlos Alarcón","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjdvQ57PQJ0x7YZm7stmKhghV4VvpxnsLPbPS4=s64","userId":"15349885202925550395"}},"outputId":"f1ab6f49-bbb9-4c9a-e7ba-32cff9b2eab8"},"source":["(train_data, train_labels), (test_data, test_labels) = mnist.load_data()"],"execution_count":null,"outputs":[{"output_type":"stream","text":["Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/mnist.npz\n","11493376/11490434 [==============================] - 0s 0us/step\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"f6t4Ofqg3nl3","executionInfo":{"status":"ok","timestamp":1615929010418,"user_tz":300,"elapsed":2336,"user":{"displayName":"Carlos Alarcón","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjdvQ57PQJ0x7YZm7stmKhghV4VvpxnsLPbPS4=s64","userId":"15349885202925550395"}},"outputId":"3212656d-15fe-4fc3-975b-e0d2fe83ff43"},"source":["train_data.shape"],"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["(60000, 28, 28)"]},"metadata":{"tags":[]},"execution_count":4}]},{"cell_type":"code","metadata":{"scrolled":true,"colab":{"base_uri":"https://localhost:8080/"},"id":"yFVAqkwN3nl4","executionInfo":{"status":"ok","timestamp":1615929010418,"user_tz":300,"elapsed":2331,"user":{"displayName":"Carlos Alarcón","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjdvQ57PQJ0x7YZm7stmKhghV4VvpxnsLPbPS4=s64","userId":"15349885202925550395"}},"outputId":"0e789d00-5a99-49e6-afa0-eca3dcedcd05"},"source":["train_data[0]"],"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([[  0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,   0,\n","         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dtype=uint8)"]},"metadata":{"tags":[]},"execution_count":5}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":282},"id":"73oWm6Ox3nl6","executionInfo":{"status":"ok","timestamp":1615929010686,"user_tz":300,"elapsed":2593,"user":{"displayName":"Carlos Alarcón","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjdvQ57PQJ0x7YZm7stmKhghV4VvpxnsLPbPS4=s64","userId":"15349885202925550395"}},"outputId":"e5d564ce-185e-4014-8f8c-1dc8918f6c47"},"source":["plt.imshow(train_data[45])\n","plt.show"],"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<function matplotlib.pyplot.show>"]},"metadata":{"tags":[]},"execution_count":6},{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAPsAAAD4CAYAAAAq5pAIAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAON0lEQVR4nO3de4xc9XnG8edhMXYx0PhC1w5xuZWbiQQhG2gANalQARNVJiQioVXkqhZLUqhABVrkqoWq/YNEhIgS6tYpbpyKEKGAiyM5Da6bBiUgw0INGEwwpSDs2l4SEy4JsY15+8ceRwvs/GY9Z27m/X6k1cycd+acl/E+nDPnN3t+jggBeO87oNcNAOgOwg4kQdiBJAg7kARhB5I4sJsbO8hTY5qmd3OTQCq/1M+1K3Z6olqtsNs+X9ItkgYk/XNE3Fh6/jRN1xk+p84mARSsi7UNay0fxtsekHSbpAWS5ku6xPb8VtcHoLPqfGY/XdKzEfFcROyS9C1JC9vTFoB2qxP2IyS9OO7x5mrZ29getj1ie2S3dtbYHIA6On42PiKWRcRQRAxN0dRObw5AA3XCvkXSvHGPP1AtA9CH6oT9YUnH2T7a9kGSPitpVXvaAtBuLQ+9RcSbtq+Q9D2NDb0tj4gn29YZgLaqNc4eEaslrW5TLwA6iK/LAkkQdiAJwg4kQdiBJAg7kARhB5Ig7EAShB1IgrADSRB2IAnCDiRB2IEkCDuQBGEHkiDsQBKEHUiCsANJEHYgCcIOJEHYgSQIO5AEYQeSIOxAEoQdSIKwA0kQdiAJwg4kQdiBJAg7kARhB5KoNWWz7eclvSZpj6Q3I2KoHU0BaL9aYa/8bkT8pA3rAdBBHMYDSdQNe0i6z/YjtocneoLtYdsjtkd2a2fNzQFoVd3D+LMjYovt35C0xvbTEXH/+CdExDJJyyTpMM+MmtsD0KJae/aI2FLdjkpaKen0djQFoP1aDrvt6bYP3Xtf0rmSNrSrMQDtVecwflDSStt71/PNiPj3tnQFoO1aDntEPCfplDb2AqCDGHoDkiDsQBKEHUiCsANJEHYgiXb8IQz62MD7fr1Yn7bqoGL9nt9aU6zvjj373NNeP/rllGL9j1df2vK6JenEpS83rO156pla694fsWcHkiDsQBKEHUiCsANJEHYgCcIOJEHYgSQYZ98PHHDoocX6K584uWHtji/eVHzt+w+cWqzvbHJtoR+8cXCxPu2A3Q1rH51WvkzZxou+Wt54E2ce9YcNa7N/v9aq90vs2YEkCDuQBGEHkiDsQBKEHUiCsANJEHYgCcbZ+8DA8ccW69tuKv8zPfjhWwvV8jj6hl3lgfTFN19VrA/e+kCxPjB7VsPaxhuPLr726QVLi/VmfvbK9Ia12bXWvH9izw4kQdiBJAg7kARhB5Ig7EAShB1IgrADSTDO3gUDM2YU66fdVb6G+V8d/mix/tiuxrU/eLB87fVjvloeZx98oDyO3szuk3+zYe2Wj32z1roX/vjCYv2Eq7c0rLV+tfv9V9M9u+3ltkdtbxi3bKbtNbY3Vbfl32YAPTeZw/ivSzr/Hcuuk7Q2Io6TtLZ6DKCPNQ17RNwvacc7Fi+UtKK6v0JS+XgKQM+1+pl9MCK2Vve3SRps9ETbw5KGJWmaytcrA9A5tc/GR0RIaniWJyKWRcRQRAxNafJHGQA6p9Wwb7c9V5Kq29H2tQSgE1oN+ypJi6r7iyTd2552AHRK08/stu+U9HFJs21vlnS9pBsl3WV7saQXJF3cySb7XbNx9C3/MqdYX3n4fcX6yM6BYn3JlZ9vWDv2Ow8VX1vXAdOmlZ/w1y81LJ138Cu1tv3GzUcU69O2d/a/fX/TNOwRcUmD0jlt7gVAB/F1WSAJwg4kQdiBJAg7kARhB5LgT1zbYNcp5UsiP/SRf6q1/j+7/vJi/X3febDW+kvizFOK9RNufbJY/+Kcle1sBzWwZweSIOxAEoQdSIKwA0kQdiAJwg4kQdiBJBhnb4Ofzm/yZ55N/OCN8uW6Zj36zksAvl2dyyL/3zVnFuu3/ck/FOvHHPh6sf7t149sWPv0IduKr/2b0Q8X69N/tKlYz3i56BL27EAShB1IgrADSRB2IAnCDiRB2IEkCDuQBOPsbTDlE40vlzwZD/3i2GJ983mzyis4r/FY+acW/VfxpQsOu6VYnzOws1gfXrC4WH/u+oMa1j591vLia+9c/5Fi/fiXHynW8Xbs2YEkCDuQBGEHkiDsQBKEHUiCsANJEHYgCcbZ2+DXlpanbFaTy8ZfO+uJcv3qcr2OJdvOKNafvqg8LbJeKf9N+rnH/KJhbd3OKcXXHr90V3nb2CdN9+y2l9setb1h3LIbbG+xvb76uaCzbQKoazKH8V+XdP4Ey78SEadWP6vb2xaAdmsa9oi4X1L5ukgA+l6dE3RX2H68Osxv+KHV9rDtEdsju1X+njWAzmk17EslHSvpVElbJX250RMjYllEDEXE0BRNbXFzAOpqKewRsT0i9kTEW5K+Jun09rYFoN1aCrvtueMeflLShkbPBdAfmo6z275T0sclzba9WdL1kj5u+1RJIel5SZd1sMe+N/3p8t+zn3T3FcX6zQvuKNYXHPzyPve014nf/UKxftI1Ta69/rMXi/WfLv5osb5y7t83rP3tS6cVX6uHOvf9goyahj0iLplg8e0d6AVAB/F1WSAJwg4kQdiBJAg7kARhB5JwRHRtY4d5Zpzhc7q2PdQ3MGtmsX7v42taXvfxqz9frl/6cMvrzmpdrNWrscMT1dizA0kQdiAJwg4kQdiBJAg7kARhB5Ig7EASXEoaRaMXnlCsv6XvFevffn1Ow9qJt/28ybrRTuzZgSQIO5AEYQeSIOxAEoQdSIKwA0kQdiAJxtlRdNGV/1nr9V/6x880rM1Z/0CtdWPfsGcHkiDsQBKEHUiCsANJEHYgCcIOJEHYgSQYZ0/uwKOPLNavnXVPsf7KW7uK9ak7ujcvAcqa7tltz7P9fdtP2X7S9pXV8pm219jeVN3O6Hy7AFo1mcP4NyVdHRHzJf22pMttz5d0naS1EXGcpLXVYwB9qmnYI2JrRDxa3X9N0kZJR0haKGlF9bQVki7sVJMA6tunz+y2j5L0IUnrJA1GxNaqtE3SYIPXDEsalqRpOrjVPgHUNOmz8bYPkXS3pKsi4tXxtRibHXLCMzERsSwihiJiaIqm1moWQOsmFXbbUzQW9DsiYu/p2e2251b1uZJGO9MigHZoehhv25Jul7QxIm4eV1olaZGkG6vbezvSITrqmcveX+v1fzf6sWJ9xooHa60f7TOZz+xnSfqcpCdsr6+WLdFYyO+yvVjSC5Iu7kyLANqhadgj4oeSJpzcXdI57W0HQKfwdVkgCcIOJEHYgSQIO5AEYQeS4E9c3+MGTi5PuXztwvLXI7bveaNYf+Yz85p08L9N6ugW9uxAEoQdSIKwA0kQdiAJwg4kQdiBJAg7kATj7O9xZ975WLG+6LAXivXNb5bXv+dZxtH3F+zZgSQIO5AEYQeSIOxAEoQdSIKwA0kQdiAJxtn3Awd88MRiff6KZxrW/nTmfzdZe/lX4FM3/XmxPqgHmqwf/YI9O5AEYQeSIOxAEoQdSIKwA0kQdiAJwg4kMZn52edJ+oakQUkhaVlE3GL7BkmXSnqpeuqSiFjdqUYzGz1zRrH+b3PWFarlf+ITv/uFYv34WxlHf6+YzJdq3pR0dUQ8avtQSY/YXlPVvhIRN3WuPQDtMpn52bdK2lrdf832RklHdLoxAO21T5/ZbR8l6UOS9h43XmH7cdvLbU94rGl72PaI7ZHd2lmrWQCtm3TYbR8i6W5JV0XEq5KWSjpW0qka2/N/eaLXRcSyiBiKiKEpmtqGlgG0YlJhtz1FY0G/IyLukaSI2B4ReyLiLUlfk3R659oEUFfTsNu2pNslbYyIm8ctnzvuaZ+UtKH97QFol8mcjT9L0uckPWF7fbVsiaRLbJ+qseG45yVd1pEOUcuSbWcU6ydds6lY39POZtBTkzkb/0NJnqDEmDqwH+EbdEAShB1IgrADSRB2IAnCDiRB2IEkHBFd29hhnhln+JyubQ/IZl2s1auxY6KhcvbsQBaEHUiCsANJEHYgCcIOJEHYgSQIO5BEV8fZbb8k6YVxi2ZL+knXGtg3/dpbv/Yl0Vur2tnbkRFx+ESFrob9XRu3RyJiqGcNFPRrb/3al0RvrepWbxzGA0kQdiCJXod9WY+3X9KvvfVrXxK9taorvfX0MzuA7un1nh1AlxB2IImehN32+bZ/bPtZ29f1oodGbD9v+wnb622P9LiX5bZHbW8Yt2ym7TW2N1W35fmcu9vbDba3VO/detsX9Ki3eba/b/sp20/avrJa3tP3rtBXV963rn9mtz0g6RlJvydps6SHJV0SEU91tZEGbD8vaSgiev4FDNu/I+l1Sd+IiA9Wy74kaUdE3Fj9j3JGRPxFn/R2g6TXez2NdzVb0dzx04xLulDSH6mH712hr4vVhfetF3v20yU9GxHPRcQuSd+StLAHffS9iLhf0o53LF4oaUV1f4XGflm6rkFvfSEitkbEo9X91yTtnWa8p+9doa+u6EXYj5D04rjHm9Vf872HpPtsP2J7uNfNTGAwIrZW97dJGuxlMxNoOo13N71jmvG+ee9amf68Lk7QvdvZEXGapAWSLq8OV/tSjH0G66ex00lN490tE0wz/iu9fO9anf68rl6EfYukeeMef6Ba1hciYkt1OypppfpvKurte2fQrW5He9zPr/TTNN4TTTOuPnjvejn9eS/C/rCk42wfbfsgSZ+VtKoHfbyL7enViRPZni7pXPXfVNSrJC2q7i+SdG8Pe3mbfpnGu9E04+rxe9fz6c8jous/ki7Q2Bn5/5H0l73ooUFfx0h6rPp5ste9SbpTY4d1uzV2bmOxpFmS1kraJOk/JM3so97+VdITkh7XWLDm9qi3szV2iP64pPXVzwW9fu8KfXXlfePrskASnKADkiDsQBKEHUiCsANJEHYgCcIOJEHYgST+H1S4IDpbSPESAAAAAElFTkSuQmCC\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"YODLfs6q3nl6","executionInfo":{"status":"ok","timestamp":1615929010687,"user_tz":300,"elapsed":2590,"user":{"displayName":"Carlos Alarcón","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjdvQ57PQJ0x7YZm7stmKhghV4VvpxnsLPbPS4=s64","userId":"15349885202925550395"}},"outputId":"f13ae100-9416-4fc9-f78c-53ebc876ebbf"},"source":["train_labels[45]"],"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["9"]},"metadata":{"tags":[]},"execution_count":7}]},{"cell_type":"markdown","metadata":{"id":"nSqO8gGW3nl6"},"source":["## Creando un modelo de datos"]},{"cell_type":"code","metadata":{"id":"rPraNF413nl7"},"source":["model = models.Sequential()\n","model.add(layers.Dense(512,activation='relu', input_shape=(28*28,)))\n","model.add(layers.Dense(10,activation='softmax'))"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"id":"__eZcERb3nl7"},"source":["model.compile(optimizer='rmsprop',\n","              loss='categorical_crossentropy',\n","              metrics=['accuracy'])"],"execution_count":null,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"TfKflwfh3nl9"},"source":["## Limpieza de datos"]},{"cell_type":"code","metadata":{"id":"9qAf4hkX3nl9"},"source":["x_train = train_data.reshape((60000,28*28))\n","x_train = x_train.astype('float32')/255\n","\n","x_test = test_data.reshape((10000,28*28))\n","x_test = x_test.astype('float32')/255"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"id":"i3fadNk83nl9"},"source":["y_train = to_categorical(train_labels)\n","y_test = to_categorical(test_labels)"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"gPIBLlk-3nl9","executionInfo":{"status":"ok","timestamp":1615929016015,"user_tz":300,"elapsed":7906,"user":{"displayName":"Carlos Alarcón","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjdvQ57PQJ0x7YZm7stmKhghV4VvpxnsLPbPS4=s64","userId":"15349885202925550395"}},"outputId":"88aeb521-f834-4b9e-eb6e-ea0d65d37ecf"},"source":["train_labels[0]"],"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["5"]},"metadata":{"tags":[]},"execution_count":12}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"FErmMYY93nl-","executionInfo":{"status":"ok","timestamp":1615929016015,"user_tz":300,"elapsed":7903,"user":{"displayName":"Carlos Alarcón","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjdvQ57PQJ0x7YZm7stmKhghV4VvpxnsLPbPS4=s64","userId":"15349885202925550395"}},"outputId":"a16ac3b9-63bc-4f51-8d8d-8e0d50a64572"},"source":["y_train[0]"],"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([0., 0., 0., 0., 0., 1., 0., 0., 0., 0.], dtype=float32)"]},"metadata":{"tags":[]},"execution_count":13}]},{"cell_type":"markdown","metadata":{"id":"z_Om7oc23nl-"},"source":["## Entrenando el modelo"]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"MmmToe7y3nl_","executionInfo":{"status":"ok","timestamp":1615929025263,"user_tz":300,"elapsed":17147,"user":{"displayName":"Carlos Alarcón","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjdvQ57PQJ0x7YZm7stmKhghV4VvpxnsLPbPS4=s64","userId":"15349885202925550395"}},"outputId":"4506a4c1-9566-46f4-88c6-1f7da96a2f8d"},"source":["model.fit(x_train, y_train, epochs=5, batch_size=128)"],"execution_count":null,"outputs":[{"output_type":"stream","text":["Epoch 1/5\n","469/469 [==============================] - 4s 2ms/step - loss: 0.4281 - accuracy: 0.8785\n","Epoch 2/5\n","469/469 [==============================] - 1s 2ms/step - loss: 0.1134 - accuracy: 0.9670\n","Epoch 3/5\n","469/469 [==============================] - 1s 3ms/step - loss: 0.0684 - accuracy: 0.9798\n","Epoch 4/5\n","469/469 [==============================] - 1s 3ms/step - loss: 0.0497 - accuracy: 0.9858\n","Epoch 5/5\n","469/469 [==============================] - 1s 2ms/step - loss: 0.0362 - accuracy: 0.9892\n"],"name":"stdout"},{"output_type":"execute_result","data":{"text/plain":["<tensorflow.python.keras.callbacks.History at 0x7faed05944d0>"]},"metadata":{"tags":[]},"execution_count":14}]},{"cell_type":"markdown","metadata":{"id":"Fi5vPFUA3nl_"},"source":["## Evaluando sobre data de test"]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"16PRKxoW3nl_","executionInfo":{"status":"ok","timestamp":1615929026062,"user_tz":300,"elapsed":17941,"user":{"displayName":"Carlos Alarcón","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjdvQ57PQJ0x7YZm7stmKhghV4VvpxnsLPbPS4=s64","userId":"15349885202925550395"}},"outputId":"4351d15d-373e-4099-f313-b094242afa70"},"source":["model.evaluate(x_test,y_test)"],"execution_count":null,"outputs":[{"output_type":"stream","text":["313/313 [==============================] - 1s 2ms/step - loss: 0.0722 - accuracy: 0.9786\n"],"name":"stdout"},{"output_type":"execute_result","data":{"text/plain":["[0.07223645597696304, 0.978600025177002]"]},"metadata":{"tags":[]},"execution_count":15}]}]}