Welcome to my Learning Projects Repository. This is a collection of interactive, web-based visualizations I've built to explore and teach core concepts in machine learning and deep learning. Each project focuses on a specific algorithm, providing an intuitive and hands-on way to understand how it works through step-by-step execution and parameter adjustment.
An interactive web-based visualization tool for the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) clustering algorithm. This project helps users understand how DBSCAN works by providing a step-by-step visual representation of the clustering process.
A visual exploration of the gradient descent optimization algorithm in two dimensions. This tool allows you to experiment with different starting points and learning rates to see how they affect the path and convergence speed towards a local minimum.
An extension of the 2D visualizer into three dimensions. This project illustrates the convergence of gradient descent on a 3D surface, offering a more spatial understanding of the optimization process. Adjust the initial point and learning rate to see the resulting descent path.
- Browse the projects listed above.
- Click the title links to access individual project repositories and use the "Live Demo" badges to interact with the tool directly in your browser.
- Each sub-repository contains its own README file with setup instructions and details about the project.
Contributions are welcome! If you'd like to suggest improvements or add a new educational project, feel free to open an issue or submit a pull request.
This repository is licensed under the MIT License. See individual sub-repositories for more details on licensing.