Learn Machine Learning with JavaScript

You already think in arrays, state, and components. Machine learning uses the same patterns, just with different names. Tensorcraft bridges the gap with 50+ analogies that map your frontend knowledge to ML concepts.

You Already Know More ML Than You Think

If you understand useState(), you understand model weights. If you can write array.map(), you can do tensor operations. If you've used fetch(), you already know how inference APIs work. The leap from frontend to ML is smaller than you think.

How Tensorcraft Works

• 1.Pick a theme: each teaches a different ML specialization through a unique story
• 2.Learn through bridges: 51 analogies map ML concepts to frontend concepts you know, each labeled where it breaks
• 3.Code in the browser: write real TensorFlow.js code in interactive exercises
• 4.Build a real project: each theme culminates in a capstone ML model running live in the browser

No Python Required

Everything runs in the browser using TensorFlow.js. You write TypeScript, test in real-time, and deploy models that work on any device with a web browser. You skip the Jupyter notebooks, pip installs, and GPU setup entirely.

Start Free

Module 1 of Deep Orbit is completely free, no account, no credit card. Just open a lesson and start learning.

Available Now

• Deep Orbit: Time-Series & Signals

Coming Soon

4 more themes ship in waves. Each has a preview page where you can join its waitlist:

• Neon Protocol: Real-Time Computer Vision (coming soon)
• Signal Ward: NLP & Text Intelligence (coming soon)
• Nova Canvas: Multimodal & Generative AI (coming soon)
• Terra Grid: Edge AI & Production ML (coming soon)

Check out our pricing to see what each plan includes.