Welcome to my machine learning projects repository! This is a collection of projects I've built while learning and exploring various concepts in machine learning, from basic implementations to more advanced applications.
ML_projects/
βββ [Project Name]/ # Each project in its own directory
β βββ readme.md # Project-specific documentation
β βββ main.py # Main application file
β βββ requirements.txt # Python dependencies (if needed)
β βββ data/ # Data files and datasets
β βββ models/ # Trained models and weights
β βββ utils/ # Utility functions and helpers
βββ README.md # Main repository documentation
βββ .gitignore # Git ignore file
Each project follows a similar structure with its own documentation, source code, and dependencies.
- Python 3.7+ (recommended: Python 3.8+)
- pip (Python package installer)
- other python packages
-
Clone the repository:
git clone <repository-url> cd ML_projects
-
Install dependencies for each project:
- AI Agent: Requires
google-generativeaiandpython-dotenvpackages - Style Transfer App: Install all dependencies from
requirements.txt - SmolGrad: No external dependencies required (pure Python implementation)
- AI Agent: Requires
-
Set up API keys (for AI Agent):
- Create a
.envfile in theAI_agent/directory - Add your Google Gemini API key:
GOOGLE_API_KEY=your_api_key_here
- Create a
Each project can be run independently. Check the individual project README files for specific usage instructions.
- Core ML: TensorFlow, NumPy, Pandas
- AI/LLM: Google Generative AI (Gemini)
- Web Development: Streamlit
- Image Processing: Pillow, OpenCV
- Utilities: python-dotenv, requests, tqdm
This is a personal learning repository, but suggestions and feedback are always welcome! Feel free to:
- Report bugs or issues
- Suggest improvements
- Share your own ML project ideas
This project is for educational purposes. Please respect the licenses of any third-party libraries and datasets used in individual projects.
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Built with β€οΈ by suraj