ANN in Python from SCRATCH

This project implements a neural network class without using any ML library.

Project Structure

.
|-- ANN/
|   |-- Layer.py
|   |-- Dense.py
|   |-- Network.py
|   |-- Activation.py
|   |-- Activation_functions/
|       |-- Tanh.py
|   |-- Loss_functions/
|       |-- MSE.py
|-- mnist_digits.py

• ANN/: Directory for your neural network classes.

  • Layer.py: Implementation of the Base Layer class.

  • Dense.py: Implementation of the Dense class.

  • Network.py: Implementation of the Network class.

  • Activation.py: Implementation of the Activation class.

  • Activation_functions/: Contains activation function implementations.

    • Tanh.py: Implementation of the hyperbolic tangent activation function.

  • Loss_functions/: Contains loss function implementations.

    • MSE.py: Implementation of the Mean Squared Error loss function.

• mnist_digits.py: Main script or application where you use the neural network.

Getting Started

1. Clone the repository:

   git clone https://github.com/sudarshanmg/ANN.git

2. Install dependencies:

   pip install -r requirements.txt

3. Run the MNIST digits script:

   python mnist_digits.py

Usage

• Modify and run mnist_digits.py to experiment with the neural network on the MNIST dataset.

Tutorial

Head to the Tutorial Section.

Contributing

Feel free to contribute to the development of this project. Create an issue or submit a pull request.

License

This project is licensed under the MIT License.