Welcome to the Machine Learning Visualizer App, an interactive full-stack platform to explore, understand, and compare machine learning algorithms through live visualizations and pseudocode walkthroughs.
⚠️ Note: This project is still in active development expect frequent updates and features!
🔗 Live App: https://machine-learning-visualizer.vercel.app
An interactive web application that lets users visually explore how different machine learning algorithms behave in real-time. Users can switch between algorithms, understand their workings through animations and pseudocode, and learn when and why to use each.
- Frontend: Next.js (React + TypeScript + Tailwind CSS + Framer Motion)
- Backend: .NET Core Web API
- Database: Firebase Realtime Database
- Containerization: Docker
- Deployment:
- Frontend: Vercel
- Backend: Render
- Visualization: D3.js or React Canvas / Chart libraries
- Authentication: JWT-based (placeholder login/register supported)
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User Authentication 🔐
- JWT issuance & protected user sessions
- Firebase Authentication integration
- Email/Password and OAuth providers (Google, GitHub)
- Protected user sessions
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Algorithm Visualizer 🤖
- Switch between ML algorithms (e.g., KNN, SVM, Decision Tree, K-Means)
- Interactive canvas: input data and see decision boundaries or clusters live
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Algorithm Docs 📄
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Each algorithm has:
- Overview
- When to use it
- How it works
- Pseudocode
- Key properties
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Learning Mode 📖
- Step-through animations explaining how data flows through the algorithm
- Optionally toggle labels, confidence, or metrics overlays
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Custom Dataset Uploads 📂 (Planned)
- Upload simple CSV files to test algorithms on your own data
- Fork the repo
- Create a feature branch:
git checkout -b feature/YourFeature - Commit your changes:
git commit -m "Add new feature" - Push to the branch:
git push origin feature/YourFeature - Open a Pull Request describing your changes and referencing any related issues