/Handwritten-Number-Classifier

Primary LanguageJupyter Notebook

MNIST Deep Learning Project

This project uses Keras and TensorFlow to classify handwritten digits from the MNIST dataset using a deep learning model.

Dataset

The MNIST dataset contains:

  • 60,000 training images
  • 10,000 test images
  • Each image is 28x28 pixels in grayscale.

Installation

  1. Clone the repository: 
    git clone https://github.com/yourusername/mnist-deep-learning.git
cd mnist-deep-learning
  2. Install dependencies: 
    pip install -r requirements.txt

Usage

Run the following command to train the model:

python train_model.py

Model

The model is a Artifical Neural Network (ANN) with several convolutional and dense layers for classification.

Results

The model achieves high accuracy on the MNIST test set.