{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "toc": true
   },
   "source": [
    "<h1>Deeplearning: Table of Contents<span class=\"tocSkip\"></span></h1>\n",
    "<div class=\"toc\"><ul class=\"toc-item\"><li><span><a href=\"#Libraries\" data-toc-modified-id=\"Libraries-1\"><span class=\"toc-item-num\">1&nbsp;&nbsp;</span>Libraries</a></span></li><li><span><a href=\"#Data---MNIST-Digit-Recognition---10-classes\" data-toc-modified-id=\"Data---MNIST-Digit-Recognition---10-classes-2\"><span class=\"toc-item-num\">2&nbsp;&nbsp;</span>Data - MNIST Digit Recognition - 10 classes</a></span><ul class=\"toc-item\"><li><span><a href=\"#Examples-of-Digits\" data-toc-modified-id=\"Examples-of-Digits-2.1\"><span class=\"toc-item-num\">2.1&nbsp;&nbsp;</span>Examples of Digits</a></span></li></ul></li><li><span><a href=\"#Convolutional-Neural-Network-(CNN)\" data-toc-modified-id=\"Convolutional-Neural-Network-(CNN)-3\"><span class=\"toc-item-num\">3&nbsp;&nbsp;</span>Convolutional Neural Network (CNN)</a></span><ul class=\"toc-item\"><li><span><a href=\"#Training,-only-2-epochs\" data-toc-modified-id=\"Training,-only-2-epochs-3.1\"><span class=\"toc-item-num\">3.1&nbsp;&nbsp;</span>Training, only 2 epochs</a></span></li><li><span><a href=\"#Prediction\" data-toc-modified-id=\"Prediction-3.2\"><span class=\"toc-item-num\">3.2&nbsp;&nbsp;</span>Prediction</a></span></li><li><span><a href=\"#Accuracy\" data-toc-modified-id=\"Accuracy-3.3\"><span class=\"toc-item-num\">3.3&nbsp;&nbsp;</span>Accuracy</a></span></li></ul></li></ul></div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-01-27T23:45:44.989383Z",
     "start_time": "2021-01-27T23:45:44.761115Z"
    }
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-01-27T23:52:01.168935Z",
     "start_time": "2021-01-27T23:52:01.164943Z"
    }
   },
   "outputs": [],
   "source": [
    "import keras\n",
    "from keras import layers"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data - MNIST Digit Recognition - 10 classes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It already comes as trainging and testing set, so you don't need to split it yourself"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-01-27T23:47:31.765497Z",
     "start_time": "2021-01-27T23:47:31.542913Z"
    }
   },
   "outputs": [],
   "source": [
    "(Xt, yt), (Xs, ys) = keras.datasets.mnist.load_data()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-01-27T23:47:45.609634Z",
     "start_time": "2021-01-27T23:47:45.601690Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((60000, 28, 28), (10000, 28, 28), (60000,), (10000,))"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Xt.shape, Xs.shape, yt.shape, ys.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Examples of Digits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-01-27T23:50:08.383945Z",
     "start_time": "2021-01-27T23:50:07.481399Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 40 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,7))\n",
    "for k in range(40):\n",
    "    plt.subplot(4,10,k+1)\n",
    "    plt.imshow(Xt[k],cmap='gray')\n",
    "    plt.axis('off')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Convolutional Neural Network (CNN)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-01-27T23:56:01.689346Z",
     "start_time": "2021-01-27T23:56:01.679373Z"
    }
   },
   "outputs": [],
   "source": [
    "def modelCNN(input_shape=(28,28,1),output=10):\n",
    "    Input = keras.Input(shape=input_shape)\n",
    "    x = layers.Conv2D(32, kernel_size=(3, 3), activation=\"relu\")(Input)\n",
    "    x = layers.MaxPooling2D(pool_size=(2, 2))(x)\n",
    "    x = layers.Conv2D(64, kernel_size=(3, 3), activation=\"relu\")(x)\n",
    "    x = layers.MaxPooling2D(pool_size=(2, 2))(x)\n",
    "    x = layers.Flatten()(x)\n",
    "    x = layers.Dropout(0.5)(x)\n",
    "    output = layers.Dense(output, activation=\"softmax\")(x)\n",
    "    \n",
    "    model = keras.models.Model(Input, output)\n",
    "    model.compile(loss=\"sparse_categorical_crossentropy\", optimizer=\"adam\", metrics=[\"accuracy\"])\n",
    "    return model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-01-28T08:47:41.769752Z",
     "start_time": "2021-01-28T08:47:41.629129Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"model_2\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "input_6 (InputLayer)         (None, 28, 28, 1)         0         \n",
      "_________________________________________________________________\n",
      "conv2d_7 (Conv2D)            (None, 26, 26, 32)        320       \n",
      "_________________________________________________________________\n",
      "max_pooling2d_3 (MaxPooling2 (None, 13, 13, 32)        0         \n",
      "_________________________________________________________________\n",
      "conv2d_8 (Conv2D)            (None, 11, 11, 64)        18496     \n",
      "_________________________________________________________________\n",
      "max_pooling2d_4 (MaxPooling2 (None, 5, 5, 64)          0         \n",
      "_________________________________________________________________\n",
      "flatten_2 (Flatten)          (None, 1600)              0         \n",
      "_________________________________________________________________\n",
      "dropout_2 (Dropout)          (None, 1600)              0         \n",
      "_________________________________________________________________\n",
      "dense_2 (Dense)              (None, 10)                16010     \n",
      "=================================================================\n",
      "Total params: 34,826\n",
      "Trainable params: 34,826\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model = modelCNN()\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-01-28T00:01:35.636330Z",
     "start_time": "2021-01-28T00:01:35.629345Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((60000, 28, 28, 1), (10000, 28, 28, 1))"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Xt = Xt[:,:,:,None]\n",
    "Xs = Xs[:,:,:,None]\n",
    "Xt.shape, Xs.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Training, only 2 epochs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-01-28T00:00:52.086476Z",
     "start_time": "2021-01-27T23:59:57.816582Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train on 60000 samples, validate on 10000 samples\n",
      "Epoch 1/2\n",
      "60000/60000 [==============================] - 27s 453us/step - loss: 0.1420 - accuracy: 0.9574 - val_loss: 0.0641 - val_accuracy: 0.9807\n",
      "Epoch 2/2\n",
      "60000/60000 [==============================] - 27s 451us/step - loss: 0.1148 - accuracy: 0.9644 - val_loss: 0.0597 - val_accuracy: 0.9817\n"
     ]
    }
   ],
   "source": [
    "history = model.fit(Xt, yt, batch_size=128, epochs=2, verbose=1,validation_data=(Xs, ys),)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Prediction"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Keras model gives you probability scores**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-01-28T00:01:44.028272Z",
     "start_time": "2021-01-28T00:01:37.846796Z"
    }
   },
   "outputs": [],
   "source": [
    "ytp = model.predict(Xt)\n",
    "ysp = model.predict(Xs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Converting probabilities to class number by computing the maximum probabilty**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-01-28T00:02:25.859883Z",
     "start_time": "2021-01-28T00:02:25.852901Z"
    }
   },
   "outputs": [],
   "source": [
    "ytpI = np.argmax(ytp,1)\n",
    "yspI = np.argmax(ysp,1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Predicted classes for first 10 training examples**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-01-28T00:02:34.198174Z",
     "start_time": "2021-01-28T00:02:34.193190Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([5, 0, 4, 1, 9, 2, 1, 3, 1, 4], dtype=int64)"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ytpI[:10]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Actual classes of first 10 training examples**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-01-28T08:51:52.893478Z",
     "start_time": "2021-01-28T08:51:52.884500Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([5, 0, 4, 1, 9, 2, 1, 3, 1, 4], dtype=uint8)"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "yt[:10]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Accuracy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-01-28T08:52:13.733927Z",
     "start_time": "2021-01-28T08:52:13.725949Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training Accuracy :  0.9851333333333333\n",
      "Testing  Accuracy :  0.9817\n"
     ]
    }
   ],
   "source": [
    "print('Training Accuracy : ',np.mean(ytpI==yt))\n",
    "print('Testing  Accuracy : ',np.mean(yspI==ys))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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