Handwritten_digit_recognisor.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "gpuType": "T4",
      "authorship_tag": "ABX9TyPmSSq6g11AEQ//laBtIFQX",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/nishikantmandal007/Hand_written_digit_recognizer/blob/main/Handwritten_digit_recognisor.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 18,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "8ohV9-PvwQl0",
        "outputId": "1f3bb57d-13c2-48b3-fe78-155f6a0c03d8"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x400 with 20 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model: \"sequential_16\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " flatten_16 (Flatten)        (None, 784)               0         \n",
            "                                                                 \n",
            " dense_36 (Dense)            (None, 128)               100480    \n",
            "                                                                 \n",
            " dense_37 (Dense)            (None, 128)               16512     \n",
            "                                                                 \n",
            " dense_38 (Dense)            (None, 10)                1290      \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 118282 (462.04 KB)\n",
            "Trainable params: 118282 (462.04 KB)\n",
            "Non-trainable params: 0 (0.00 Byte)\n",
            "_________________________________________________________________\n",
            "Epoch 1/10\n",
            "1875/1875 - 6s - loss: 0.2295 - accuracy: 0.9321 - 6s/epoch - 3ms/step\n",
            "Epoch 2/10\n",
            "1875/1875 - 4s - loss: 0.0995 - accuracy: 0.9690 - 4s/epoch - 2ms/step\n",
            "Epoch 3/10\n",
            "1875/1875 - 4s - loss: 0.0685 - accuracy: 0.9783 - 4s/epoch - 2ms/step\n",
            "Epoch 4/10\n",
            "1875/1875 - 5s - loss: 0.0514 - accuracy: 0.9834 - 5s/epoch - 3ms/step\n",
            "Epoch 5/10\n",
            "1875/1875 - 4s - loss: 0.0424 - accuracy: 0.9859 - 4s/epoch - 2ms/step\n",
            "Epoch 6/10\n",
            "1875/1875 - 5s - loss: 0.0327 - accuracy: 0.9891 - 5s/epoch - 2ms/step\n",
            "Epoch 7/10\n",
            "1875/1875 - 5s - loss: 0.0292 - accuracy: 0.9901 - 5s/epoch - 2ms/step\n",
            "Epoch 8/10\n",
            "1875/1875 - 4s - loss: 0.0250 - accuracy: 0.9912 - 4s/epoch - 2ms/step\n",
            "Epoch 9/10\n",
            "1875/1875 - 5s - loss: 0.0216 - accuracy: 0.9927 - 5s/epoch - 3ms/step\n",
            "Epoch 10/10\n",
            "1875/1875 - 4s - loss: 0.0199 - accuracy: 0.9934 - 4s/epoch - 2ms/step\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "313/313 [==============================] - 1s 2ms/step - loss: 0.1009 - accuracy: 0.9788\n",
            "Test accuracy: 0.9787999987602234\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "1/1 [==============================] - 0s 62ms/step\n",
            "The result is : 7\n"
          ]
        }
      ],
      "source": [
        "import tensorflow as tf\n",
        "from tensorflow import keras\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# Load the MNIST dataset\n",
        "mnist = keras.datasets.mnist\n",
        "(train_images, train_labels), (test_images, test_labels) = mnist.load_data()\n",
        "\n",
        "# Preprocess the data\n",
        "train_images = train_images / 255.0\n",
        "test_images = test_images / 255.0\n",
        "\n",
        "# Show a sample of training images\n",
        "fig, axes = plt.subplots(2, 10, figsize=(10, 4))\n",
        "fig.suptitle('Training Set', fontsize=10)\n",
        "axes = axes.ravel()\n",
        "for i in range(20):\n",
        "    axes[i].imshow(train_images[i], cmap='gray')\n",
        "    axes[i].axis('off')\n",
        "plt.show()\n",
        "\n",
        "# Define the model architecture\n",
        "model = keras.Sequential([\n",
        "    keras.layers.Flatten(input_shape=(28, 28)),\n",
        "    keras.layers.Dense(128, activation='relu'),\n",
        "    keras.layers.Dense(128, activation='relu'),\n",
        "    keras.layers.Dense(10, activation='softmax')\n",
        "])\n",
        "\n",
        "# Compile the model\n",
        "model.compile(optimizer='adam',\n",
        "              loss='sparse_categorical_crossentropy',\n",
        "              metrics=['accuracy'])\n",
        "\n",
        "# Print the model summary\n",
        "model.summary()\n",
        "\n",
        "# Train the model and track the accuracy history\n",
        "epochs = 10\n",
        "history = model.fit(train_images, train_labels, epochs=epochs, verbose=2)\n",
        "\n",
        "# Plot the training accuracy\n",
        "plt.plot(history.history['accuracy'])\n",
        "plt.title('Model Training Accuracy')\n",
        "plt.xlabel('Epoch')\n",
        "plt.ylabel('Accuracy')\n",
        "plt.show()\n",
        "\n",
        "# Evaluate the model\n",
        "test_loss, test_acc = model.evaluate(test_images, test_labels)\n",
        "print('Test accuracy:', test_acc)\n",
        "\n",
        "# Test with an image and print the prediction\n",
        "image_index = 0\n",
        "test_image = test_images[image_index]\n",
        "plt.imshow(test_image, cmap='gray')\n",
        "plt.axis('off')\n",
        "plt.show()\n",
        "\n",
        "prediction = model.predict(test_image.reshape(1, 28, 28))\n",
        "predicted_label = prediction.argmax()\n",
        "print('The result is :', predicted_label)\n"
      ]
    }
  ]
}