Axon

a fun new way to learn Machine Learning

Learn ML the way it should be taught.

Machine Learning done right. Bite-sized lessons. Real intuition. A small glitchy cube named Tensor who is way too excited to teach you backprop. No textbook, no 3-hour MOOCs, no jargon walls.

Also coming toAndroid· spring '26

  • no textbooks
  • 500 lessons
  • made by humans
  • machine learning
  • gradients welcome

poke me. i dare you.

Meet your gradient buddy

Hi, I'm Tensor.

I'm an undertrained model who gained sentience and is earnestly excited to help you learn machine learning. I'm fluent in math, still figuring out humans. I glitch when surprised or wrong — that's just how the gradients hit. I will never say "great job!"when you didn't.

  • short answers
  • no scolding
  • occasional puns
  • never sarcastic

FAQ · Pacing

How many problems should you do a day?

don't click here
don't think about it

How it works

Three loops, then you ship.

  • 01Lesson 02 · descent

    Touch the math.

    Drag a ball down a loss curve. Tap a point to flip a class. Math becomes muscle memory before it becomes notation.

    A ball resting on the left slope of a loss curve, with a drag arrow pointing downhillx = -1.40 · loss = 0.712 · step 0
  • 02Lesson 06 · separable

    Get one rep wrong.

    Tensor glitches the second you pick the wrong answer. No "try again!" cheerleading — just a one-line fix and the next rep.

    Two clusters of dots split by a dashed line
  • 03Lesson 12 · matmul

    Build the small thing.

    Every five lessons, you make something tiny that runs. A perceptron. A classifier. Then a transformer block. Then your own.

Inside a lesson

5-minute reps. Real intuition.

Each lesson is a tiny interactive moment — drag, drop, click, wrong, right, next. You don't watch ML. You touch it until it sticks.

  1. Vectors as arrows you can pull
  2. Loss as a hill the ball rolls down
  3. Backprop as a chain of nudges
  4. Attention as a spotlight you can aim
LESSON 06 · 4/12

Tap a point to flip its class. Watch the line refit.

A scatter plot: coral dots on the left, lavender dots on the right, split by a dashed boundary
"Linearly separable. The line knows."