About the platform

GradVex turns a neural network into a visible, playable system.

The project is built as an educational full-stack-style web app for the AI era: a live playground, visual architecture explorer, math panel, 3D scene, and guided explanations that make weights, biases, activations, loss, and predictions concrete.

Learn by doing

Every concept connects back to a real action in the playground.

Local and fast

The trained model runs in-browser after the weight files load.

Inspectable math

Users can move from intuition to formulas without leaving the app.

Model details

Architecture

MLP 784 -> 128 -> 64 -> 10

Parameters

109,386

Training data

MNIST, 60k train / 10k test

Loss

Categorical cross-entropy

Inference

Runs locally in the browser

Purpose

Explain neural networks through interaction

Technology stack

Next.js 16App Router and production build
React 19Interactive client components
TensorFlow.js 4In-browser neural network inference
Three.js3D network visualization
ZustandShared UI and model state
Tailwind CSS 4Responsive design system
GitHub profile