u/nightmareofai

I've been making steady improvements to Confluence over the past few months, and I'd love to get more feedback from people who use machine learning.

The project lets you explore algorithms through interactive visualizations instead of static examples. You can compare models, switch between datasets, adjust hyperparameters, and see how different algorithms behave using real scikit-learn computation.

I'm always looking for ideas on what could be improved, whether it's the UI, features, learning experience, or anything else.

If you have a few minutes, I'd really appreciate it if you could give it a try and share your thoughts.

Website: https://confluence.website

GitHub: https://github.com/mahirmlk/Confluence

Hi everyone,

For the last few weeks, I've been building a project called Confluence.

I originally started it because I struggled to build intuition while learning machine learning. I found myself constantly switching between notebooks, documentation, videos, and different visualization tools, and none of them really brought everything together.

The goal wasn't to replace scikit-learn or Jupyter notebooks. Instead, I wanted a place where I could experiment and immediately see what changing a hyperparameter actually does.

At the moment, the project includes:

• 38 machine learning algorithms
• 25 datasets (real-world + synthetic)
• Interactive decision boundary visualizations
• Training animations
• Prediction explanations
• Side-by-side algorithm comparison
• Algorithm encyclopedia
• Python code generation for experiments

Everything runs on a FastAPI backend using real scikit-learn models rather than browser-only simulations.

I'd really appreciate feedback from people who work with ML regularly.

What features would make a tool like this genuinely useful for learning or teaching machine learning?

Website:
https://confluence.website

GitHub:
https://github.com/mahirmlk/Confluence