Neural-Networks

Overview

This project demonstrates the use of neural networks to classify images from the American Sign Language (ASL) dataset. The repository showcases a machine learning pipeline, from data preprocessing to model training and evaluation, implemented in Python using Jupyter Notebook.

Features

• Data loading and preprocessing for the ASL dataset
• Neural network modeling and training
• Evaluation and visualization of model performance
• Example notebook for reproducibility

Installation

1. Clone the repository:

   git clone https://github.com/Vignesh-Kamsala/Neural-Networks.git
   cd Neural-Networks

2. Install required dependencies:

   • It is recommended to use a virtual environment.
   • Install dependencies (example using pip):

     pip install -r requirements.txt

   • If requirements.txt is not present, typical dependencies may include:

     numpy
     pandas
     matplotlib
     scikit-learn
     tensorflow or pytorch
     jupyter
     

Usage

• Open the main notebook:

  jupyter notebook asl-project.ipynb

• Follow the notebook instructions to train and evaluate the neural network on the ASL dataset.

Repository Structure

• asl-project.ipynb - Main Jupyter notebook for model training and evaluation
• README.md - Project documentation

Contributing

Contributions are welcome! Please open an issue or submit a pull request for improvements or bug fixes.

License

This project currently does not have a license. Please add a license if you intend to share or reuse the code.

Contact

For questions or collaborations, please contact Vignesh-Kamsala.

---

Project created December 2024.