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Repository Organization Guide

This repository is organized into the following main categories:

Main Categories

1. Algorithms and Deep Learning Models

Implementation of various ML algorithms
Deep learning model architectures
Neural network implementations

2. Classification Models

Binary and multi-class classification projects
Text classification
Image classification

3. Detection Models

Object detection
Anomaly detection
Face detection

4. Generative AI & LLMs

Large Language Models
Text generation
Image generation

5. NLP (Natural Language Processing)

Text processing
Sentiment analysis
Language models

6. Computer Vision

Image processing
Video analysis
OpenCV projects

7. Prediction Models

Time series prediction
Regression models
Forecasting

8. Recommendation Models

Collaborative filtering
Content-based systems
Hybrid systems

Project Structure

Each project should follow the template provided in /docs/project_template/

Contributing

Choose the appropriate category for your project
Follow the project template structure
Ensure proper documentation
Include requirements.txt
Add proper README.md

Notes for Contributors

Keep datasets in separate data directories
Include clear installation instructions
Document model performance
Add visualizations when possible