Image Classification with TensorFlow

Project Description

This project demonstrates image classification using the MNIST dataset with TensorFlow. The MNIST dataset is a collection of 70,000 handwritten digits, which are divided into training and testing sets. The goal of this project is to train a neural network to recognize and classify these handwritten digits.

Installation Instructions

1. Clone the repository:

   git clone https://github.com/Drexregion/ImageClassification

2. Navigate to the project directory:

   cd https://github.com/Drexregion/ImageClassification

3. Install the required dependencies:

   pip install -r requirements.txt

Usage

1. Run the Jupyter notebook:

   jupyter notebook ImageClassification.ipynb

2. Follow the steps in the notebook to load the MNIST dataset, preprocess the data, build the model, and train it.

Dependencies

• Python 3.x
• TensorFlow
• NumPy

License

This project is licensed under the MIT License. See the LICENSE file for more details.