A collection of machine learning and data science projects for learning and experimentation.
Exploring dimensionality reduction techniques with interactive visualizations.
Projects:
- t-SNE Visualization: Animated visualization of t-SNE algorithm on MNIST digits dataset
- 5000-iteration optimization with frame-by-frame animation
- Comprehensive Jupyter notebook with detailed explanations
- Based on O'Reilly's illustrated t-SNE tutorial
Technologies: Python, scikit-learn, matplotlib, seaborn, moviepy
Each project folder contains:
- Detailed README with project-specific information
requirements.txtfor dependencies- Setup and usage instructions
- Jupyter notebooks with comprehensive documentation
More projects will be added to this repository covering:
- Supervised learning
- Unsupervised learning
- Deep learning
- Natural language processing
- Computer vision
- Time series analysis
- And more!
Each project includes references to tutorials, papers, and documentation used.
Note: This is a learning repository. Code is for educational purposes and may not be production-ready.
Last updated: February 2026