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Deep Orbit is live · No Python required

ML Speaks JavaScript.Turns Out You're Fluent.

Skip the Python tax. Learn ML the way you already build, in JavaScript, right in the browser, and walk out with a model you can actually ship. The instincts behind state and caching are what ML runs on.

11 modules · 56 lessons · 1 deployable model

No credit card. No account for module 1.

Learn machine learning for frontend developers with JavaScript and TensorFlow.js, browser-based ML tutorials, TensorFlow JS courses, and Transformers.js guides.

THE BRIDGE SYSTEM

Every ML Concept Has a Frontend Name

YOUR REACT CODE

Component props

function Card({ title, image }) { return <div>{title}</div>; }
ML EQUIVALENT

Training data

const trainData = tf.tensor2d(features); model.fit(trainData, labels)

What You'll Build

By Module 11: a real-time anomaly detection system, trained, tested, and deployed entirely in the browser.

Learn more →
Train

Neural networks built layer by layer in TensorFlow.js, trained in your tab. The tab is the whole toolchain, Python never enters it.

Detect

Real-time signals classified normal or anomalous by an autoencoder + LSTM ensemble you assemble yourself.

Deploy

A working model that runs entirely client-side, 60fps inference on an ordinary laptop via WebGL.

Own

Solved exercises push to your GitHub as commits (any paid theme). Walk into interviews able to explain every layer.

CHOOSE YOUR WORLD
LIVE NOW

Five Worlds

Same ML syllabus. Five story universes. Deep Orbit is live; the other four ship in waves.

Deep Orbit
Time-Series & Signals

Navigate the unknown through signals

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Before you ask

Fair Questions, Honest Answers

Can I learn machine learning with JavaScript?

Yes. Tensorcraft teaches machine learning entirely in JavaScript and TypeScript using TensorFlow.js. Models train and run in the browser, no Python required. The curriculum covers neural networks, LSTMs, CNNs, and transformers through hands-on tutorials built for frontend developers.

How does Tensorcraft teach ML to frontend developers?

Through 50+ 'bridge' analogies that map frontend concepts you already know (like useState, Array.map, and fetch) to their ML equivalents (model weights, tensor operations, and inference APIs). Each course is a story-driven narrative where you build real ML models.

How much math do I need?

None upfront. You need working JavaScript: comfortable with functions, arrays, and async. The math is there when you want it: derivations sit in optional expandable drawers, and you can finish every module without opening one.

Is Tensorcraft free?

Module 1 of Deep Orbit, the live theme, is free, no account or credit card required. The other four themes ship in waves, each with a waitlist. Full themes cost $59 each, with bundle discounts available up to $159 for all 5 themes.

What ML topics does Tensorcraft cover?

Five specializations: Time-Series & Signals (RNNs, LSTMs), Computer Vision (CNNs, YOLO), NLP & Text Intelligence (Transformers, BERT), Multimodal & Generative AI (GANs, Diffusion), and Edge AI & Production ML (quantization, MLOps).

What if it turns out not to be for me?

Module 1 is free before any money moves. After purchase there's a 14-day money-back guarantee: full refund if you've used less than 20% of a theme.

module 1 · free · no account required

Bridge
the gap.

Open the lesson and start reading. If it clicks, the full theme is $59 once, no subscription.

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