PPolySim OS
Use case · powered by Gradient Descent

Gradient Descent for a convolutional net

Simulate a convolutional net live in your browser. This runs the real Gradient Descent solver — adjust the inputs, watch it respond instantly, and export the result. No install, no account.

Gradient Descent StudioLive

Controls

Watch gradient descent (with momentum) roll downhill on different loss landscapes. Too high a learning rate overshoots.

Presets

▶ Run in Python

Data Inspector

Surfaceripple
Step0/200
Optimizermomentum GD

Governing equation

Reading this result: A learning rate of 3 is well matched to the curvature here: steps are large enough to make progress yet small enough to avoid overshoot, giving a smooth, roughly quadratic descent toward the minimum.

Runs locally in your browser — free forever. Scale to the cloud when reality gets heavy.

or unlock everything with Pro →

About this simulation

The full Gradient Descent tool models a convolutional net with the same numerics engineers and scientists use — running entirely client-side. Change any parameter and the result updates in real time, so you can build intuition, check a design, or teach the concept without spreadsheets or installs.

More you can do with Gradient Descent

Other ways to simulate a convolutional net

Frequently asked questions

How do I simulate a convolutional net?
Open this page and use the live Gradient Descent tool below — set your inputs and the simulation runs instantly in your browser using real numerics. No install, no account needed.
Is it free?
Yes. The simulation runs free in your browser. A one-time unlock or a Pro plan adds advanced parameters, saved presets, data import, and clean exports.
Can I use my own numbers?
Absolutely — every input is adjustable, and with data import you can drive a convolutional net from your own measurements.