Fashion_MNIST.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "hV3opIdiaEft"
   },
   "source": [
    "# Importing Necessary Libraries"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# STUDENT ID:13146946\n",
    "# Name: Chaitanya Sai Kumar Tummalapalli"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "id": "iTGzyw4hZA9y"
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "%matplotlib inline\n",
    "import IPython.display\n",
    "import PIL.Image\n",
    "import psutil,os\n",
    "from tensorflow.keras import models, layers\n",
    "from tensorflow.keras.layers import Dense, Dropout\n",
    "from tensorflow.keras.utils import plot_model\n",
    "from tensorflow.keras.optimizers import Adam, RMSprop\n",
    "from tensorflow.keras.utils import to_categorical"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "zjK3utjIa3Zt"
   },
   "source": [
    "# Loading Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "id": "dqIz_ZbaaNbJ"
   },
   "outputs": [],
   "source": [
    "from tensorflow.keras.datasets import fashion_mnist\n",
    "\n",
    "(train_images, train_labels), (test_images, test_labels) = fashion_mnist.load_data()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "hVcZaU71bIVF"
   },
   "source": [
    "# Data Exploration and Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "Hri-PYDfgPd6",
    "outputId": "49af63a3-49ac-4fad-b875-049dac1634bb"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(60000, 28, 28)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_images.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "M5ogP_t7gYHw",
    "outputId": "d9619928-0dfe-4424-de23-dd04639957ad"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(10000, 28, 28)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_images.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "d0xW5OsWa7Db",
    "outputId": "2714edd5-1109-4404-f150-13ee79af2ab4"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The target classes for the classification task are:\n",
      "0 : T-shirt/top\n",
      "1 : Trouser\n",
      "2 : Pullover\n",
      "3 : Dress\n",
      "4 : Coat\n",
      "5 : Sandal\n",
      "6 : Shirt\n",
      "7 : Sneaker\n",
      "8 : Bag\n",
      "9 : Ankle boot\n"
     ]
    }
   ],
   "source": [
    "classes = {0 : \"T-shirt/top\",\n",
    "        1 : \"Trouser\", \n",
    "        2 : \"Pullover\", \n",
    "        3 : \"Dress\", \n",
    "        4 : \"Coat\", \n",
    "        5 : \"Sandal\", \n",
    "        6 : \"Shirt\", \n",
    "        7 : \"Sneaker\", \n",
    "        8 : \"Bag\", \n",
    "        9 : \"Ankle boot\"}\n",
    "print(\"The target classes for the classification task are:\")\n",
    "for key in classes.keys():\n",
    "  print(str(key) + \" : \" + classes[key])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 354
    },
    "id": "8sXfZifld1T-",
    "outputId": "f3beb004-3fb8-43c4-cacb-02ae79451f39"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1440x360 with 30 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (20, 5))\n",
    "plot = 1\n",
    "\n",
    "for i in range(31):\n",
    "    if plot < 31:\n",
    "        ax = plt.subplot(3, 10, plot)\n",
    "        plt.imshow(train_images[i], cmap = 'binary')\n",
    "        plt.axis('off')\n",
    "        plt.title(classes[train_labels[i]], fontdict = {'fontsize'  : 12, 'color' : 'black'})\n",
    "        \n",
    "    plot += 1\n",
    "  \n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "A9-WApDRhBFM"
   },
   "source": [
    "# Data Preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "id": "O0g3r5Xwg3ka"
   },
   "outputs": [],
   "source": [
    "train_images = train_images.astype('float32') / 255\n",
    "test_images = test_images.astype('float32') / 255"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "id": "D2I3Fa0zhC88"
   },
   "outputs": [],
   "source": [
    "train_labels = to_categorical(train_labels)\n",
    "test_labels = to_categorical(test_labels)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "wPLtJVlVxkiW"
   },
   "source": [
    "# Model Training and Results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "ZmwFkxmUhE18",
    "outputId": "f2ddf02b-f417-4acb-f09f-65d949dce23d"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"sequential\"\n",
      "_________________________________________________________________\n",
      " Layer (type)                Output Shape              Param #   \n",
      "=================================================================\n",
      " flatten (Flatten)           (None, 784)               0         \n",
      "                                                                 \n",
      " dense (Dense)               (None, 300)               235500    \n",
      "                                                                 \n",
      " dropout (Dropout)           (None, 300)               0         \n",
      "                                                                 \n",
      " dense_1 (Dense)             (None, 200)               60200     \n",
      "                                                                 \n",
      " dropout_1 (Dropout)         (None, 200)               0         \n",
      "                                                                 \n",
      " dense_2 (Dense)             (None, 100)               20100     \n",
      "                                                                 \n",
      " dense_3 (Dense)             (None, 10)                1010      \n",
      "                                                                 \n",
      "=================================================================\n",
      "Total params: 316,810\n",
      "Trainable params: 316,810\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model = models.Sequential([\n",
    "    layers.Flatten(input_shape = [28, 28, ]),\n",
    "    layers.Dense(300, activation = 'relu'),\n",
    "    layers.Dropout(0.3),\n",
    "    layers.Dense(200, activation = 'relu'),\n",
    "    layers.Dropout(0.3),\n",
    "    layers.Dense(100, activation = 'relu'),\n",
    "    layers.Dense(10, activation = 'softmax')\n",
    "    ])\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 865
    },
    "id": "ML2bRIl_jVDa",
    "outputId": "1f049ceb-027e-426e-e935-b99df7de9573"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_model(model, show_shapes = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "id": "V_E-0sq9jdjR"
   },
   "outputs": [],
   "source": [
    "model.compile(optimizer = Adam(), loss = 'categorical_crossentropy', metrics = 'accuracy')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "0OtEFRjHkGoY",
    "outputId": "d29df714-4178-4bc7-a72c-1286b8648ed7"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/15\n",
      "1875/1875 [==============================] - 11s 5ms/step - loss: 0.5767 - accuracy: 0.7905 - val_loss: 0.4569 - val_accuracy: 0.8363\n",
      "Epoch 2/15\n",
      "1875/1875 [==============================] - 10s 5ms/step - loss: 0.4376 - accuracy: 0.8407 - val_loss: 0.4213 - val_accuracy: 0.8460\n",
      "Epoch 3/15\n",
      "1875/1875 [==============================] - 7s 4ms/step - loss: 0.4027 - accuracy: 0.8527 - val_loss: 0.3718 - val_accuracy: 0.8669\n",
      "Epoch 4/15\n",
      "1875/1875 [==============================] - 6s 3ms/step - loss: 0.3809 - accuracy: 0.8613 - val_loss: 0.3688 - val_accuracy: 0.8653\n",
      "Epoch 5/15\n",
      "1875/1875 [==============================] - 7s 4ms/step - loss: 0.3645 - accuracy: 0.8675 - val_loss: 0.3720 - val_accuracy: 0.8667\n",
      "Epoch 6/15\n",
      "1875/1875 [==============================] - 6s 3ms/step - loss: 0.3511 - accuracy: 0.8702 - val_loss: 0.3521 - val_accuracy: 0.8756\n",
      "Epoch 7/15\n",
      "1875/1875 [==============================] - 8s 4ms/step - loss: 0.3435 - accuracy: 0.8738 - val_loss: 0.3395 - val_accuracy: 0.8785\n",
      "Epoch 8/15\n",
      "1875/1875 [==============================] - 10s 5ms/step - loss: 0.3335 - accuracy: 0.8777 - val_loss: 0.3373 - val_accuracy: 0.8788\n",
      "Epoch 9/15\n",
      "1875/1875 [==============================] - 7s 4ms/step - loss: 0.3300 - accuracy: 0.8794 - val_loss: 0.3348 - val_accuracy: 0.8801\n",
      "Epoch 10/15\n",
      "1875/1875 [==============================] - 7s 4ms/step - loss: 0.3187 - accuracy: 0.8817 - val_loss: 0.3326 - val_accuracy: 0.8815\n",
      "Epoch 11/15\n",
      "1875/1875 [==============================] - 7s 4ms/step - loss: 0.3133 - accuracy: 0.8836 - val_loss: 0.3354 - val_accuracy: 0.8797\n",
      "Epoch 12/15\n",
      "1875/1875 [==============================] - 7s 4ms/step - loss: 0.3083 - accuracy: 0.8867 - val_loss: 0.3416 - val_accuracy: 0.8759\n",
      "Epoch 13/15\n",
      "1875/1875 [==============================] - 6s 3ms/step - loss: 0.3013 - accuracy: 0.8881 - val_loss: 0.3316 - val_accuracy: 0.8796\n",
      "Epoch 14/15\n",
      "1875/1875 [==============================] - 7s 4ms/step - loss: 0.2978 - accuracy: 0.8896 - val_loss: 0.3255 - val_accuracy: 0.8812\n",
      "Epoch 15/15\n",
      "1875/1875 [==============================] - 7s 4ms/step - loss: 0.2930 - accuracy: 0.8920 - val_loss: 0.3369 - val_accuracy: 0.8812\n"
     ]
    }
   ],
   "source": [
    "model_history = model.fit(train_images, train_labels, validation_data = (test_images, test_labels), epochs = 15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "9jDcAQpQtxFO",
    "outputId": "6d281e22-9eb1-4b8e-a440-4349316e2b1f"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "313/313 [==============================] - 1s 2ms/step - loss: 0.3369 - accuracy: 0.8812\n",
      "Test Accuracy:  0.8812000155448914\n",
      "Test loss:  0.33694398403167725\n"
     ]
    }
   ],
   "source": [
    "test_loss, test_accuracy = model.evaluate(test_images, test_labels)\n",
    "print('Test Accuracy: ', test_accuracy)\n",
    "print('Test loss: ',test_loss)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 683
    },
    "id": "86JtDq5OkMda",
    "outputId": "c0a155d1-6b60-4a72-aada-dac438a7a090"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15, 5))\n",
    "plt.plot(model_history.history['val_accuracy'])\n",
    "plt.title('Validation accuracy')\n",
    "plt.ylabel('Accuracy')\n",
    "plt.xlabel('Epoch')\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(15, 5))\n",
    "plt.plot(model_history.history['val_loss'])\n",
    "plt.title('Validation loss')\n",
    "plt.ylabel('Loss')\n",
    "plt.xlabel('Epoch')\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "accelerator": "GPU",
  "colab": {
   "provenance": []
  },
  "gpuClass": "standard",
  "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": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}