Learn math by building it.
No code. Just nodes.

Drag nodes onto a canvas. Wire them together. From basic arithmetic to training neural networks — no programming, no memorizing. Just connect and understand.

Start simple.

Constant
3
Constant
5
Add
Number Display

No code. Just drag, connect, and understand.

131 components. Infinite combinations.

From arithmetic to neural networks — every concept is a node you can wire.

Change one value...

Everything recomputes. Instantly.

Click once. Gradients flow everywhere.

x = 2
2 ∇ 6
+ 1
3 ∇ 6
x² (Loss)
9 ∇ 1

Set any node as a loss function, press the gradient button, and watch backpropagation happen — no code, just the chain rule applied automatically.

No programming. No syntax. No debugging.

No memorizing formulas you'll forget tomorrow.

Just drag nodes, wire them together — and watch math click.

65+ hands-on lessons. Zero code.

Step-by-step interactive lessons built right into the canvas. Drag sliders, change values, watch everything update.

Foundations

  • What is a function?
  • The unit circle
  • Taylor series
  • Composing functions

Statistics

  • Variance and std dev
  • Linear regression and R²
  • The box plot
  • Seeing distributions

Deep Learning

  • Backpropagation on a wire
  • Gradient descent in action
  • Build a neural network layer
  • Train a network — click Step and watch it learn

Physics

  • Projectile motion
  • Ohm's law
  • The pendulum
  • Wave superposition

Bill Co

3rd year student · University of Victoria Data Scientist Co-op · Government of British Columbia
Connect on LinkedIn

I started building Statslingo because too many people think they're bad at math — when really, they just need a better format than staring at equations.

We're great at connecting things and playing with systems. So I built a place where you can learn everything from addition to backpropagation just by dragging nodes and wiring them together. No code. No syntax errors. Just math you can see and touch.

I hope you enjoy it.

Changelog

v2.0Vector-Matrix BridgeApr 2026
  • 13 new components for seamless scalar/vector/matrix transitions
  • In-app Component Reference with search, examples, and formulas
  • Full gradient support for all new bridge components
v1.4Training & Deep LearningApr 2026
  • Train a Neural Network lesson with live forward/backward pass
  • Guided demo system with animated walkthroughs
v1.3Autodiff & GradientsApr 2026
  • Reverse-mode automatic differentiation through any graph
  • One-click training with gradient descent
View full changelog →

Ready to connect?

Launch Statslingo →

Free. No account required. No code needed. Just start building.