Created a no-code ML platform; designed for developers to develop quick prototypes for ML pipelines fast and for beginners without coding experience who are looking to learn ML.

Key features: automatic shape calculations when connecting layers to each other, built-in metrics & inference windows, and ability to export to pure PyTorch.

Tech Stack: Built with Python, PyTorch, and DearPyGui.

The Goal: This isn't meant to replace production code, but to make prototyping architectures feel more like sketching.

I'd love to hear your thoughts on this approach. I've worked on this project for a while and I'm looking for feedback on what direction to go: beginner appeal or more developer oriented.