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.
- Clone the repository:
git clone https://github.com/Drexregion/ImageClassification
- Navigate to the project directory:
cd https://github.com/Drexregion/ImageClassification - Install the required dependencies:
pip install -r requirements.txt
- Run the Jupyter notebook:
jupyter notebook ImageClassification.ipynb
- Follow the steps in the notebook to load the MNIST dataset, preprocess the data, build the model, and train it.
- Python 3.x
- TensorFlow
- NumPy
This project is licensed under the MIT License. See the LICENSE file for more details.