https://github.com/arpan132002/fitness-tracker-using-smart-watches

This repository contains the code for a full machine learning project that tracks fitness activities. The project demonstrates the process of building a fitness tracker using Python and machine learning techniques
https://github.com/arpan132002/fitness-tracker-using-smart-watches

deep-neural-networks machine-learning outlier-detection

Last synced: about 1 month ago
JSON representation

This repository contains the code for a full machine learning project that tracks fitness activities. The project demonstrates the process of building a fitness tracker using Python and machine learning techniques

• Host: GitHub
• URL: https://github.com/arpan132002/fitness-tracker-using-smart-watches
• Owner: arpan132002
• Created: 2024-07-05T10:30:23.000Z (6 months ago)
• Default Branch: main
• Last Pushed: 2024-08-05T12:49:38.000Z (5 months ago)
• Last Synced: 2024-08-05T14:44:00.744Z (5 months ago)
• Topics: deep-neural-networks, machine-learning, outlier-detection
• Language: Python
• Homepage:
• Size: 1.22 MB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
# Fitness Tracker ML

This repository contains the code for a full machine learning project that tracks fitness activities. The project demonstrates the process of building a fitness tracker using Python and machine learning techniques.

## Project Overview

In this project, I created a fitness tracker application that takes accelerometer data and gyroscope data & uses machine learning to analyze and predict fitness activities. The application includes the following features:

- Data collection and preprocessing

- Building and training a machine learning model

- Evaluating the model

- Deploying the model in a fitness tracker application

## Requirements

- Python 3.7+

- Libraries: pandas, numpy, scikit-learn, tensorflow, matplotlib, etc.