Heartbeat Harmony Analyzer

Overview

The Heartbeat Harmony Analyzer is a project aimed at analyzing heartbeat data using machine learning techniques. This project implements a Multi-Layer Perceptron (MLP) from scratch, incorporating various algorithms including backpropagation, Resilient Propagation, ADAM Optimizer, and Bayesian Network. Additionally, custom metrics and a data loader have been developed to facilitate the analysis process.

Features

Multi-Layer Perceptron (MLP): Implemented from scratch, the MLP forms the core of the heartbeat data analysis.
Algorithms:
Backpropagation: A classic algorithm used for training neural networks by propagating error gradients backward.
Resilient Propagation: A variant of backpropagation known for its adaptive learning rate.
ADAM Optimizer: A popular optimization algorithm that combines momentum and adaptive learning rates.
Bayesian Network: Utilized for probabilistic modeling and inference, providing insights into the relationship between heartbeat data and health indicators.
Custom Metrics: Developed metrics specifically tailored for evaluating the performance of the heartbeat harmony analyzer.
Data Loader: A custom data loader designed to efficiently load and preprocess heartbeat data for analysis.

Usage

Installation

Clone the repository:

bash git clone https://github.com/your_username/heartbeat-harmony-analyzer.git

Install the required dependencies:

bash pip install -r requirements.txt

Running the Analyzer

Navigate to the project directory:

bash cd heartbeat-harmony-analyzer

Run the main script to start the heartbeat analysis:

bash python main.py

Contributing

Contributions to the Heartbeat Harmony Analyzer project are welcome! If you have any ideas for improvements, new features, or bug fixes, please submit a pull request.

Acknowledgments

Special thanks to Mohamad Shehab - Sami AL-Omar - Rama Alsobt - Alaa Kaissi - Hiba Sallam - William AL-Odeh - Blqees Ghazr Al-Deen - Yazan Monther for their contributions and support.
This project was inspired by Vladislav Kruglikov.