SVHN_Classification_Neural_Network_.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "_Upxzt7efZsd"
   },
   "source": [
    "# Street View House Numbers (SVHN) image classification"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "Xhemwms4fzLu"
   },
   "source": [
    "## Problem Statement"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "mpEQKWLIf9IK"
   },
   "source": [
    "Street View House Numbers (SHVN) is a real-world image dataset that consists of images obtained from house numbers in Google street view images. The dataset can be used to automatically transcribe an address number from a geo-located patch of pixels and the associated transcribed number can be used to pinpoint the location of the building it represents.\n",
    "\n",
    "The challenge in transcribing text from images is that the visual appearance of text in the image dataset varies based on large range of fonts, colours, styles, orientation and character arrangements. The problem is further complicated by environmental factors such as lighting, shadows, secularities and occlusions as well as image acquisition factors such as resolution, motion and focus blurs."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "X3ohVzWMjuOk"
   },
   "source": [
    "### Objective"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "JtalD_uzjy8A"
   },
   "source": [
    "The objective of the project is to learn how to implement a simple image classification pipeline based on deep neural network using Street View House Numbers (SVHN) dataset.\n",
    "\n",
    "The goals of this project are as follows:\n",
    "\n",
    "\n",
    "\n",
    "1.   Load Dataset\n",
    "2.   Understand the basic Image Classification pipeline and the data-driven approach (train/predict stages)\n",
    "3. Data fetching and understand the train/val/test splits.\n",
    "4. Implement and apply a deep neural network classifier including (feedforward neural network, RELU, activations)\n",
    "5. Implement batch normalization for training the neural network\n",
    "6. Print the classification accuracy metrics\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "2T8y4RMGzGoy"
   },
   "source": [
    "# Project Implementation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "qDtZzrLLzQ6i"
   },
   "source": [
    "### Import necessary libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "t3XDLkfWfhVO"
   },
   "outputs": [],
   "source": [
    "import tensorflow as tf\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import logging\n",
    "import random\n",
    "import h5py\n",
    "import os\n",
    "from tensorflow.keras.utils import to_categorical\n",
    "from tensorflow.keras.models import Sequential\n",
    "from tensorflow.keras.layers import Dense, BatchNormalization, Dropout\n",
    "from tensorflow.keras.callbacks import EarlyStopping, ModelCheckpoint, TensorBoard\n",
    "from tensorflow.keras.optimizers import SGD, Adam, Nadam\n",
    "from tensorflow.keras.preprocessing.image import ImageDataGenerator"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "sltlaZyT1zKE"
   },
   "source": [
    "### Add setting for libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "ADOIYBAwzyen"
   },
   "outputs": [],
   "source": [
    "#Turn off warnings\n",
    "logging.disable(logging.WARNING)\n",
    "\n",
    "#Draw plots inline\n",
    "%matplotlib inline\n",
    "\n",
    "# Set seed for random\n",
    "random.seed(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "SGqthQoc271E"
   },
   "source": [
    "### Load the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "adjnOcQo2TG3"
   },
   "outputs": [],
   "source": [
    "#Open the file\n",
    "data = h5py.File('SVHN_single_grey1.h5')\n",
    "\n",
    "#Load the training and test data\n",
    "X_train = data['X_train'][:]\n",
    "y_train = data['y_train'][:]\n",
    "X_test = data['X_test'][:]\n",
    "y_test = data['y_test'][:]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "pd4LIxkJ4p-r"
   },
   "source": [
    "### Understand the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "id": "7Rtk_a4x4pqH",
    "outputId": "1631420e-b9e7-42e1-9fd5-bc46ed8cfb29"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(42000, 32, 32)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "YBQhFBdw61po"
   },
   "source": [
    "**The training dataset has 42k images of size 32*32**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "id": "p8Bd8qc34Fdp",
    "outputId": "369d0a6b-3e4a-4ee8-f906-aa9666f97b15"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(42000,)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_train.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "TaFynnLq7PXq"
   },
   "source": [
    "**There are 42k labels that provides the correct classification for images in our training dataset**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "id": "MXg5SzgS42wa",
    "outputId": "384a6d13-dbf1-4635-d584-95ef635726f7"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(18000, 32, 32)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_test.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "aDeZAAt37l5o"
   },
   "source": [
    "**The test dataset has 18k images of size 32*32**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "id": "AeIndGAU447z",
    "outputId": "d44fa7f6-ef20-4bd4-8de6-1375bb7b5580"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(18000,)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_test.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "T7C0uukV72kd"
   },
   "source": [
    "**There are 18k labels that provides the correct classification for images in our test dataset**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "HLbvRN6T8TWs"
   },
   "source": [
    "#### Display the first 12 images of training dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 336
    },
    "colab_type": "code",
    "id": "uBUp1a1V48pS",
    "outputId": "1a863636-b61b-4f5c-d269-20da88a6232d"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#set the size of the plot\n",
    "plt.figure(figsize=(6,6))\n",
    "\n",
    "for index in range(12):\n",
    "  plt.subplot(4,4, index+1)\n",
    "  plt.imshow(X_train[index], cmap='Greys')\n",
    "  plt.axis('off')\n",
    "\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "frp-2oly9kBw"
   },
   "source": [
    "#### Display the labels of first 12 images of training dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "id": "VKzBLlXS9Qao",
    "outputId": "9740d747-be49-41c3-f2b3-42e7cdb5d77d"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([2, 6, 7, 4, 4, 0, 3, 0, 7, 3, 1, 0], dtype=uint8)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_train[0:12]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "VC0FXwKx9_6V"
   },
   "source": [
    "**The challenge in recognizing the images is evident from the above sample as some of the images are blur while others have multiple digits displayed. Also the same digit may appear different in different images**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "nNbxhF7F_W5y"
   },
   "source": [
    "### Data Pre-Processing"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "JolMa_fC_3Rh"
   },
   "source": [
    "The following steps will be performed as part of data pre-processing\n",
    "\n",
    "1.   Flatten the data\n",
    "2.   Normalize the data\n",
    "3.   Change the labels to one hot encoding\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "tG1zVJKAIgmE"
   },
   "source": [
    "#### Flatten the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "7jYO1OIU9sVg"
   },
   "outputs": [],
   "source": [
    "#Flatten the images on both training and test to 1024 as the image size is 32*32\n",
    "X_train_flatten = X_train.reshape(X_train.shape[0], 1024).astype('float32')\n",
    "X_test_flatten = X_test.reshape(X_test.shape[0], 1024).astype('float32')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "id": "oiRBsPC2BlBI",
    "outputId": "ffc2a0f5-9318-4d1b-ef40-c30632cd55be"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(42000, 1024)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train_flatten.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "id": "GE-GsMiIB8hS",
    "outputId": "21ca14ba-1872-4981-aef2-6022ade21800"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(18000, 1024)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_test_flatten.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "52y1rR1eIniP"
   },
   "source": [
    "#### Normalize the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 51
    },
    "colab_type": "code",
    "id": "zJQ7gBGqCA8v",
    "outputId": "6a90df75-e099-47a8-fa68-21d4786b0455"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([33.0704, 30.2601, 26.852 , ..., 49.6682, 50.853 , 53.0377],\n",
       "      dtype=float32)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check the data of the first image in the training dataset\n",
    "X_train_flatten[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "AJwZsZIACzf7"
   },
   "source": [
    "The above data shows the pixel values for first image. These values range from 0 to 255. Hence to normalize the data (we need to change the values to range between 0 and 1) we will divide each of them by 255"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "M463b__7CjVe"
   },
   "outputs": [],
   "source": [
    "#Normalize the data\n",
    "X_train_norm = X_train_flatten/255\n",
    "X_test_norm = X_test_flatten/255"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 51
    },
    "colab_type": "code",
    "id": "ehNm9EmrEJA8",
    "outputId": "278cc93b-4656-43c8-c75e-c9e47be87aa7"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.12968785, 0.11866706, 0.10530196, ..., 0.19477727, 0.19942354,\n",
       "       0.20799099], dtype=float32)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Verify that data of the first image in the training dataset\n",
    "X_train_norm[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "7jBW23waJzrq"
   },
   "outputs": [],
   "source": [
    "#Delete X_train_flatten and X_test_flatten as it won't be used anymore\n",
    "del(X_train_flatten, X_test_flatten)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "SXC7BpnKIrWj"
   },
   "source": [
    "#### One hot encoding of labels"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "DcIiX8CHIxce"
   },
   "source": [
    "The output of the network needs to classify the images between 0 to 9 i.e there are 10 classes. The loss function used in our neural network will be cross entropy which expects the data in one hot encoding."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "KFCLw6KWExp1"
   },
   "outputs": [],
   "source": [
    "n_classes = 10\n",
    "y_train_enc = to_categorical(y_train, n_classes)\n",
    "y_test_enc = to_categorical(y_test, n_classes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "id": "90ZlLVGpKRRj",
    "outputId": "6cf55f6b-332d-4554-e63d-cbdc083076ea"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0., 0., 1., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_train_enc[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "AWnmyxOKLX59"
   },
   "source": [
    "The above label from the training data denotes the label for digit 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "_1FjC6RfLyoq"
   },
   "source": [
    "### Design the neural network architecure"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "zKn081raMSnE"
   },
   "source": [
    "The neural network architecture design will have the following propoerties\n",
    "\n",
    "**Input Layer :**\n",
    "\n",
    "* No. of neurons : **1024**\n",
    "\n",
    "\n",
    "**Hidden Layer 1 :**\n",
    "\n",
    "* No. of neurons : **64**\n",
    "\n",
    "* Activation Function : **ReLU**\n",
    "\n",
    "* Batch Normalization : **Yes**\n",
    "\n",
    "**Hidden Layer 2 :**\n",
    "\n",
    "* No. of neurons : **64**\n",
    "\n",
    "* Activation Function : **ReLU**\n",
    "\n",
    "* Batch Normalization : **Yes**\n",
    "\n",
    "**Hidden Layer 3 :**\n",
    "\n",
    "* No. of neurons : **32**\n",
    "\n",
    "* Activation Function : **ReLU**\n",
    "\n",
    "* Batch Normalization : **Yes**\n",
    "\n",
    "* Dropout : **0.3**\n",
    "\n",
    "**Output Layer :**\n",
    "\n",
    "* No. of neurons : **10**\n",
    "\n",
    "* Activation Function : **Softmax**\n",
    "\n",
    "\n",
    "**Additional properties of neural network**\n",
    "\n",
    "* Optimizer : **SGD**\n",
    "\n",
    "* Learning rate : **0.01**\n",
    "\n",
    "* Loss Function : **Cross Entropy**\n",
    "\n",
    "* Batch Size : **60**\n",
    "\n",
    "* Epoch : **25**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "vBX8KFd5SpCk"
   },
   "source": [
    "#### Define the architecture"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "-pzwXGs8LTzL"
   },
   "outputs": [],
   "source": [
    "# Define a sequential model\n",
    "model = Sequential()\n",
    "\n",
    "#First Hidden Layer\n",
    "model.add(Dense(64, activation='relu', input_shape=(1024,)))\n",
    "\n",
    "#Add batch normalization\n",
    "model.add(BatchNormalization())\n",
    "\n",
    "#Second Hidden Layer\n",
    "model.add(Dense(64, activation='relu'))\n",
    "\n",
    "#Add batch normalization\n",
    "model.add(BatchNormalization())\n",
    "\n",
    "# Third Hidden Layer\n",
    "model.add(Dense(32, activation='relu'))\n",
    "\n",
    "#Add batch normalization\n",
    "model.add(BatchNormalization())\n",
    "\n",
    "# Add dropout of 30% for regularization\n",
    "model.add(Dropout(0.3))\n",
    "\n",
    "#Output layer\n",
    "model.add(Dense(10, activation='softmax'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "5WBas8E0St8d"
   },
   "source": [
    "#### Model Summary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 425
    },
    "colab_type": "code",
    "id": "6DdffZNfSl-6",
    "outputId": "f1fd6f43-044f-4455-b1d9-7ac241c246ea"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"sequential\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "dense (Dense)                (None, 64)                65600     \n",
      "_________________________________________________________________\n",
      "batch_normalization (BatchNo (None, 64)                256       \n",
      "_________________________________________________________________\n",
      "dense_1 (Dense)              (None, 64)                4160      \n",
      "_________________________________________________________________\n",
      "batch_normalization_1 (Batch (None, 64)                256       \n",
      "_________________________________________________________________\n",
      "dense_2 (Dense)              (None, 32)                2080      \n",
      "_________________________________________________________________\n",
      "batch_normalization_2 (Batch (None, 32)                128       \n",
      "_________________________________________________________________\n",
      "dropout (Dropout)            (None, 32)                0         \n",
      "_________________________________________________________________\n",
      "dense_3 (Dense)              (None, 10)                330       \n",
      "=================================================================\n",
      "Total params: 72,810\n",
      "Trainable params: 72,490\n",
      "Non-trainable params: 320\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "d3n78am2TE_R"
   },
   "source": [
    "Here we have 72,490 trainable parameters and our training data has 42,000 images which may lead to overfitting. The architecture has introduced 30% dropout in the final hidden layer to regularize and avoid overfitting"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "nogX9hl0dMWd"
   },
   "source": [
    "### Configure the model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "vW9-3CQ1dWmo"
   },
   "source": [
    "#### Compile the model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "wo7e0u7CSzlV"
   },
   "outputs": [],
   "source": [
    "# The model will use SGD as optimizer with learning rate of 0.01 and cross entropy as loss function\n",
    "model.compile(optimizer=SGD(learning_rate=0.01), loss='categorical_crossentropy', metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "MHUrlfmKeQiD"
   },
   "source": [
    "#### Define output path for logs and callbacks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "-9hQCQndeJF-"
   },
   "outputs": [],
   "source": [
    "output_dir = 'Model_Output/'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "R96oeS9Hea0n"
   },
   "outputs": [],
   "source": [
    "run_name = 'regression_baseline'\n",
    "output_path = output_dir + run_name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "j3UueoELero0"
   },
   "outputs": [],
   "source": [
    "#Define a model checkpoint callback which will be used to save weights for each spoch\n",
    "modelcheckpoint = ModelCheckpoint(output_path + '/weights.{epoch:02d}.hdf5', save_weights_only=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "# If the directory does not exist, create the directory\n",
    "if not os.path.exists(output_path):\n",
    "    os.makedirs(output_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "miPjvHv_fvNR"
   },
   "outputs": [],
   "source": [
    "#Define tensorboard log file\n",
    "tensorboard = TensorBoard(log_dir='logs/' + run_name)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "vJVtGwhagJ87"
   },
   "source": [
    "### Train the model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 884
    },
    "colab_type": "code",
    "id": "0lVMnEn_gDuQ",
    "outputId": "e52a61b3-3cd6-418b-870a-c2b3974d8b59"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train on 42000 samples, validate on 18000 samples\n",
      "Epoch 1/25\n",
      "42000/42000 [==============================] - 2s 44us/sample - loss: 2.0677 - accuracy: 0.2941 - val_loss: 1.6607 - val_accuracy: 0.4461\n",
      "Epoch 2/25\n",
      "42000/42000 [==============================] - 1s 28us/sample - loss: 1.4938 - accuracy: 0.5089 - val_loss: 1.3473 - val_accuracy: 0.5685\n",
      "Epoch 3/25\n",
      "42000/42000 [==============================] - 1s 27us/sample - loss: 1.3076 - accuracy: 0.5805 - val_loss: 1.3819 - val_accuracy: 0.5351\n",
      "Epoch 4/25\n",
      "42000/42000 [==============================] - 1s 26us/sample - loss: 1.2143 - accuracy: 0.6163 - val_loss: 1.1431 - val_accuracy: 0.6371\n",
      "Epoch 5/25\n",
      "42000/42000 [==============================] - 1s 28us/sample - loss: 1.1462 - accuracy: 0.6443 - val_loss: 1.1268 - val_accuracy: 0.6461\n",
      "Epoch 6/25\n",
      "42000/42000 [==============================] - 1s 27us/sample - loss: 1.0985 - accuracy: 0.6587 - val_loss: 1.3141 - val_accuracy: 0.5876\n",
      "Epoch 7/25\n",
      "42000/42000 [==============================] - 1s 26us/sample - loss: 1.0621 - accuracy: 0.6708 - val_loss: 1.2236 - val_accuracy: 0.6098\n",
      "Epoch 8/25\n",
      "42000/42000 [==============================] - 1s 27us/sample - loss: 1.0211 - accuracy: 0.6845 - val_loss: 0.9512 - val_accuracy: 0.7010\n",
      "Epoch 9/25\n",
      "42000/42000 [==============================] - 1s 26us/sample - loss: 1.0078 - accuracy: 0.6871 - val_loss: 0.9784 - val_accuracy: 0.6960\n",
      "Epoch 10/25\n",
      "42000/42000 [==============================] - 1s 26us/sample - loss: 0.9889 - accuracy: 0.6958 - val_loss: 1.2171 - val_accuracy: 0.6278\n",
      "Epoch 11/25\n",
      "42000/42000 [==============================] - 1s 26us/sample - loss: 0.9552 - accuracy: 0.7064 - val_loss: 1.1320 - val_accuracy: 0.6339\n",
      "Epoch 12/25\n",
      "42000/42000 [==============================] - 1s 26us/sample - loss: 0.9271 - accuracy: 0.7161 - val_loss: 1.0316 - val_accuracy: 0.6657\n",
      "Epoch 13/25\n",
      "42000/42000 [==============================] - 1s 26us/sample - loss: 0.9054 - accuracy: 0.7217 - val_loss: 0.8312 - val_accuracy: 0.7454\n",
      "Epoch 14/25\n",
      "42000/42000 [==============================] - 1s 26us/sample - loss: 0.8813 - accuracy: 0.7273 - val_loss: 0.8058 - val_accuracy: 0.7521\n",
      "Epoch 15/25\n",
      "42000/42000 [==============================] - 1s 26us/sample - loss: 0.8827 - accuracy: 0.7283 - val_loss: 1.1550 - val_accuracy: 0.6359\n",
      "Epoch 16/25\n",
      "42000/42000 [==============================] - 1s 26us/sample - loss: 0.8669 - accuracy: 0.7353 - val_loss: 0.8056 - val_accuracy: 0.7463\n",
      "Epoch 17/25\n",
      "42000/42000 [==============================] - 1s 26us/sample - loss: 0.8492 - accuracy: 0.7406 - val_loss: 0.7953 - val_accuracy: 0.7553\n",
      "Epoch 18/25\n",
      "42000/42000 [==============================] - 1s 26us/sample - loss: 0.8378 - accuracy: 0.7444 - val_loss: 0.9110 - val_accuracy: 0.7048\n",
      "Epoch 19/25\n",
      "42000/42000 [==============================] - 1s 29us/sample - loss: 0.8337 - accuracy: 0.7467 - val_loss: 0.8815 - val_accuracy: 0.7234\n",
      "Epoch 20/25\n",
      "42000/42000 [==============================] - 1s 26us/sample - loss: 0.8301 - accuracy: 0.7462 - val_loss: 0.9395 - val_accuracy: 0.7026\n",
      "Epoch 21/25\n",
      "42000/42000 [==============================] - 1s 26us/sample - loss: 0.8165 - accuracy: 0.7506 - val_loss: 0.8117 - val_accuracy: 0.7445\n",
      "Epoch 22/25\n",
      "42000/42000 [==============================] - 1s 26us/sample - loss: 0.7978 - accuracy: 0.7576 - val_loss: 1.0253 - val_accuracy: 0.6821\n",
      "Epoch 23/25\n",
      "42000/42000 [==============================] - 1s 27us/sample - loss: 0.7887 - accuracy: 0.7624 - val_loss: 0.7554 - val_accuracy: 0.7626\n",
      "Epoch 24/25\n",
      "42000/42000 [==============================] - 1s 26us/sample - loss: 0.7815 - accuracy: 0.7621 - val_loss: 0.8222 - val_accuracy: 0.7456\n",
      "Epoch 25/25\n",
      "42000/42000 [==============================] - 1s 29us/sample - loss: 0.7714 - accuracy: 0.7644 - val_loss: 0.7185 - val_accuracy: 0.7783\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<tensorflow.python.keras.callbacks.History at 0x17906e240>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Train the model with batch size of 60 (which means each batch will have 700 images) and epoch of 25. \n",
    "model.fit(X_train_norm, y_train_enc, batch_size=60, epochs=25, verbose=1, callbacks=[modelcheckpoint, tensorboard], validation_data=(X_test_norm, y_test_enc))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "2NSQBW0wjUat"
   },
   "source": [
    "The best performance of our model is on epoch 25 with validation accuracy of ~78%. We will change some aspects of our model architecture to see if we can increase the accuracy."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Model Optimization"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We need to fine tune the architecture. We will make the following changes to architecture\n",
    "\n",
    "1) One additional hidden layer\n",
    "\n",
    "2) Increase the number of neurons to 128 in first hidden layer\n",
    "\n",
    "3) Activation = 'selu'\n",
    "\n",
    "4) No batch normalization (normalization taken care by selu activation)\n",
    "\n",
    "5) No dropouts\n",
    "\n",
    "6) Optimizer = 'nadam'\n",
    "\n",
    "7) Batch Size = 40"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**The neural network architecture design will have the following propoerties**\n",
    "\n",
    "**Input Layer :**\n",
    "\n",
    "* No. of neurons : **1024**\n",
    "\n",
    "\n",
    "**Hidden Layer 1 :**\n",
    "\n",
    "* No. of neurons : **128**\n",
    "\n",
    "* Activation Function : **selu**\n",
    "\n",
    "* kernel_initializer : **lecun_normal**\n",
    "\n",
    "* Batch Normalization : **No**\n",
    "\n",
    "**Hidden Layer 2 :**\n",
    "\n",
    "* No. of neurons : **64**\n",
    "\n",
    "* Activation Function : **selu**\n",
    "\n",
    "* kernel_initializer : **lecun_normal**\n",
    "\n",
    "* Batch Normalization : **No**\n",
    "\n",
    "**Hidden Layer 3 :**\n",
    "\n",
    "* No. of neurons : **64**\n",
    "\n",
    "* Activation Function : **selu**\n",
    "\n",
    "* kernel_initializer : **lecun_normal**\n",
    "\n",
    "* Batch Normalization : **No**\n",
    "\n",
    "**Hidden Layer 3 :**\n",
    "\n",
    "* No. of neurons : **32**\n",
    "\n",
    "* Activation Function : **selu**\n",
    "\n",
    "* kernel_initializer : **lecun_normal**\n",
    "\n",
    "* Batch Normalization : **No**\n",
    "\n",
    "\n",
    "**Output Layer :**\n",
    "\n",
    "* No. of neurons : **10**\n",
    "\n",
    "* Activation Function : **Softmax**\n",
    "\n",
    "\n",
    "**Additional properties of neural network**\n",
    "\n",
    "* Optimizer : **nadam**\n",
    "\n",
    "* Loss Function : **Cross Entropy**\n",
    "\n",
    "* Batch Size : **40**\n",
    "\n",
    "* Epoch : **25**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Define the architecture"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define a sequential model\n",
    "model = Sequential()\n",
    "\n",
    "#First Hidden Layer\n",
    "model.add(Dense(128, kernel_initializer='lecun_normal', activation='selu', input_shape=(1024,)))\n",
    "\n",
    "\n",
    "#Second Hidden Layer\n",
    "model.add(Dense(64, kernel_initializer='lecun_normal', activation='selu'))\n",
    "\n",
    "\n",
    "# Third Hidden Layer\n",
    "model.add(Dense(64, kernel_initializer='lecun_normal', activation='selu'))\n",
    "\n",
    "\n",
    "# Fourth Hidden Layer\n",
    "model.add(Dense(32, kernel_initializer='lecun_normal', activation='selu'))\n",
    "\n",
    "\n",
    "#Output layer\n",
    "model.add(Dense(10, activation='softmax'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The model architecture is not using batch normalization as selu activation normalizes the data within the activation function itself. Since selu uses custom weight initialization, the model architecture uses lecun_normal as weight initialization."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Model summary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"sequential_1\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "dense_4 (Dense)              (None, 128)               131200    \n",
      "_________________________________________________________________\n",
      "dense_5 (Dense)              (None, 64)                8256      \n",
      "_________________________________________________________________\n",
      "dense_6 (Dense)              (None, 64)                4160      \n",
      "_________________________________________________________________\n",
      "dense_7 (Dense)              (None, 32)                2080      \n",
      "_________________________________________________________________\n",
      "dense_8 (Dense)              (None, 10)                330       \n",
      "=================================================================\n",
      "Total params: 146,026\n",
      "Trainable params: 146,026\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Configure the model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "# The model will use nadam as optimizer and cross entropy as loss function\n",
    "model.compile(optimizer='nadam', loss='categorical_crossentropy', metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Change the path of logs and create directory"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "run_name = 'regression_Nadam'\n",
    "output_path = output_dir + run_name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "# If the directory does not exist, create the directory\n",
    "if not os.path.exists(output_path):\n",
    "    os.makedirs(output_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Define a model checkpoint callback which will be used to save weights for each spoch\n",
    "modelcheckpoint = ModelCheckpoint(output_path + '/weights.{epoch:02d}.hdf5', save_weights_only=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Define tensorboard log file\n",
    "tensorboard = TensorBoard(log_dir='logs/' + run_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train on 42000 samples, validate on 18000 samples\n",
      "Epoch 1/25\n",
      "42000/42000 [==============================] - 3s 63us/sample - loss: 1.9709 - accuracy: 0.2795 - val_loss: 1.4937 - val_accuracy: 0.5042\n",
      "Epoch 2/25\n",
      "42000/42000 [==============================] - 2s 53us/sample - loss: 1.2431 - accuracy: 0.5945 - val_loss: 1.1070 - val_accuracy: 0.6477\n",
      "Epoch 3/25\n",
      "42000/42000 [==============================] - 2s 50us/sample - loss: 1.0406 - accuracy: 0.6685 - val_loss: 0.9712 - val_accuracy: 0.6985\n",
      "Epoch 4/25\n",
      "42000/42000 [==============================] - 2s 52us/sample - loss: 0.9324 - accuracy: 0.7069 - val_loss: 0.9068 - val_accuracy: 0.7148\n",
      "Epoch 5/25\n",
      "42000/42000 [==============================] - 2s 52us/sample - loss: 0.8620 - accuracy: 0.7295 - val_loss: 0.8341 - val_accuracy: 0.7434\n",
      "Epoch 6/25\n",
      "42000/42000 [==============================] - 2s 53us/sample - loss: 0.8109 - accuracy: 0.7459 - val_loss: 0.8020 - val_accuracy: 0.7564\n",
      "Epoch 7/25\n",
      "42000/42000 [==============================] - 2s 52us/sample - loss: 0.7695 - accuracy: 0.7602 - val_loss: 0.7712 - val_accuracy: 0.7599\n",
      "Epoch 8/25\n",
      "42000/42000 [==============================] - 2s 52us/sample - loss: 0.7328 - accuracy: 0.7701 - val_loss: 0.8202 - val_accuracy: 0.7443\n",
      "Epoch 9/25\n",
      "42000/42000 [==============================] - 2s 52us/sample - loss: 0.6999 - accuracy: 0.7829 - val_loss: 0.7303 - val_accuracy: 0.7743\n",
      "Epoch 10/25\n",
      "42000/42000 [==============================] - 2s 53us/sample - loss: 0.6748 - accuracy: 0.7912 - val_loss: 0.8026 - val_accuracy: 0.7494\n",
      "Epoch 11/25\n",
      "42000/42000 [==============================] - 2s 52us/sample - loss: 0.6542 - accuracy: 0.7961 - val_loss: 0.7196 - val_accuracy: 0.7782\n",
      "Epoch 12/25\n",
      "42000/42000 [==============================] - 2s 53us/sample - loss: 0.6357 - accuracy: 0.8018 - val_loss: 0.7540 - val_accuracy: 0.7688\n",
      "Epoch 13/25\n",
      "42000/42000 [==============================] - 2s 52us/sample - loss: 0.6164 - accuracy: 0.8076 - val_loss: 0.7034 - val_accuracy: 0.7889\n",
      "Epoch 14/25\n",
      "42000/42000 [==============================] - 2s 52us/sample - loss: 0.6001 - accuracy: 0.8097 - val_loss: 0.6720 - val_accuracy: 0.7944\n",
      "Epoch 15/25\n",
      "42000/42000 [==============================] - 2s 55us/sample - loss: 0.5885 - accuracy: 0.8174 - val_loss: 0.6476 - val_accuracy: 0.8056\n",
      "Epoch 16/25\n",
      "42000/42000 [==============================] - 2s 54us/sample - loss: 0.5792 - accuracy: 0.8179 - val_loss: 0.7221 - val_accuracy: 0.7803\n",
      "Epoch 17/25\n",
      "42000/42000 [==============================] - 2s 55us/sample - loss: 0.5675 - accuracy: 0.8202 - val_loss: 0.6561 - val_accuracy: 0.8043\n",
      "Epoch 18/25\n",
      "42000/42000 [==============================] - 2s 56us/sample - loss: 0.5532 - accuracy: 0.8273 - val_loss: 0.6722 - val_accuracy: 0.7971\n",
      "Epoch 19/25\n",
      "42000/42000 [==============================] - 2s 52us/sample - loss: 0.5433 - accuracy: 0.8278 - val_loss: 0.6520 - val_accuracy: 0.8043\n",
      "Epoch 20/25\n",
      "42000/42000 [==============================] - 2s 51us/sample - loss: 0.5315 - accuracy: 0.8313 - val_loss: 0.6501 - val_accuracy: 0.8069\n",
      "Epoch 21/25\n",
      "42000/42000 [==============================] - 2s 53us/sample - loss: 0.5285 - accuracy: 0.8338 - val_loss: 0.6236 - val_accuracy: 0.8159\n",
      "Epoch 22/25\n",
      "42000/42000 [==============================] - 2s 52us/sample - loss: 0.5163 - accuracy: 0.8383 - val_loss: 0.6229 - val_accuracy: 0.8141\n",
      "Epoch 23/25\n",
      "42000/42000 [==============================] - 2s 52us/sample - loss: 0.5126 - accuracy: 0.8383 - val_loss: 0.6584 - val_accuracy: 0.8054\n",
      "Epoch 24/25\n",
      "42000/42000 [==============================] - 2s 53us/sample - loss: 0.5088 - accuracy: 0.8389 - val_loss: 0.6161 - val_accuracy: 0.8126\n",
      "Epoch 25/25\n",
      "42000/42000 [==============================] - 2s 50us/sample - loss: 0.4965 - accuracy: 0.8415 - val_loss: 0.6537 - val_accuracy: 0.8084\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<tensorflow.python.keras.callbacks.History at 0x15b692c88>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Train the model with batch size of 40 (which means each batch will have 1050 images) and epoch of 25. \n",
    "model.fit(X_train_norm, y_train_enc, batch_size=40, epochs=25, verbose=1, callbacks=[modelcheckpoint, tensorboard], validation_data=(X_test_norm, y_test_enc))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The best validation accuracy that we achieved was on epoch 21 where the accuracy was ~82%."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Load the weights from 21st epoch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "model.load_weights(output_path +'/weights.21.hdf5')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualizing some predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 144x144 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Label for the above image:  4\n",
      "Predicted label for above image:  [4]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 144x144 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Label for the above image:  8\n",
      "Predicted label for above image:  [8]\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 144x144 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Label for the above image:  7\n",
      "Predicted label for above image:  [7]\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 144x144 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Label for the above image:  6\n",
      "Predicted label for above image:  [6]\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 144x144 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Label for the above image:  3\n",
      "Predicted label for above image:  [3]\n"
     ]
    }
   ],
   "source": [
    "plt.figure(figsize=(2,2))\n",
    "plt.imshow(X_test[13], cmap=\"gray\")\n",
    "plt.show()\n",
    "\n",
    "print(\"Label for the above image: \", y_test[13])\n",
    "print(\"Predicted label for above image: \", model.predict_classes(X_test[13].reshape(1,1024)))\n",
    "\n",
    "\n",
    "plt.figure(figsize=(2,2))\n",
    "plt.imshow(X_test[240], cmap=\"gray\")\n",
    "plt.show()\n",
    "\n",
    "print(\"Label for the above image: \", y_test[240])\n",
    "print(\"Predicted label for above image: \", model.predict_classes(X_test[240].reshape(1,1024)))\n",
    "\n",
    "\n",
    "\n",
    "plt.figure(figsize=(2,2))\n",
    "plt.imshow(X_test[1980], cmap=\"gray\")\n",
    "plt.show()\n",
    "\n",
    "print(\"Label for the above image: \", y_test[1980])\n",
    "print(\"Predicted label for above image: \", model.predict_classes(X_test[1980].reshape(1,1024)))\n",
    "\n",
    "\n",
    "\n",
    "plt.figure(figsize=(2,2))\n",
    "plt.imshow(X_test[7645], cmap=\"gray\")\n",
    "plt.show()\n",
    "\n",
    "print(\"Label for the above image: \", y_test[7645])\n",
    "print(\"Predicted label for above image: \", model.predict_classes(X_test[7645].reshape(1,1024)))\n",
    "\n",
    "\n",
    "plt.figure(figsize=(2,2))\n",
    "plt.imshow(X_test[12000], cmap=\"gray\")\n",
    "plt.show()\n",
    "\n",
    "print(\"Label for the above image: \", y_test[12000])\n",
    "print(\"Predicted label for above image: \", model.predict_classes(X_test[12000].reshape(1,1024)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Conclusion"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In our initial model architecture validation accuracy was ~78%. After making the following change our accuracy jumped by 4% to 82%\n",
    "\n",
    "\n",
    "1) Added one additional hidden layer\n",
    "\n",
    "2) Increased the number of neurons in first hidden layer to 128\n",
    "\n",
    "3) selu activation function used\n",
    "\n",
    "4) Removed batch normalization (normalization taken care by selu activation)\n",
    "\n",
    "5) Removed dropouts\n",
    "\n",
    "6) nadam optimizer used\n",
    "\n",
    "7) Batch Size of 40 was used (1050 images used per batch)\n",
    "\n",
    "We can futher increase the accuracy of our model by using convolutional layers. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Comparing the performance of two models"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Since we have used tensorboard and logged the performance of both the neural networks that we created, we can check the graphs in tensorboard to evaluate the performance"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Epoch accuracy graph"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The dark blue curve is for first model and light blue curve is for second model. We can see there is a difference in validation accuracy with second model performing better than the first one. Also the model validation accuracy during epochs vary a lot with first model and the second model is more consistent"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Epoch loss graph"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The dark blue curve is for first model and light blue curve is for second model. Again the second model performed better than the first model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "accelerator": "GPU",
  "colab": {
   "collapsed_sections": [],
   "name": "SVHN Classification_Neural Network .ipynb",
   "provenance": [],
   "toc_visible": true
  },
  "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": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}