Train Deep Learning

Below is a curated view of the ConvNetJS Intro → Browser Demos section so you can jump straight into hands-on neural-network experiments inside the browser. Each tile opens the vendored local copy of the original Stanford demos in a new tab—no installs or external network dependency needed.

Screenshot of MNIST digit classifier demo

MNIST CNN

Train a convolutional net that recognizes handwritten digits.

Screenshot of CIFAR10 classifier demo

CIFAR-10 CNN

Classify natural images from CIFAR-10 with a deeper convolutional net.

Screenshot of interactive 2D classifier demo

2-D Classifier

Draw toy datasets and watch a small net learn decision boundaries live.

Screenshot of 1D regression demo

1-D Regression

Interactively fit smooth curves to 1-D data using neural nets.

Screenshot of autoencoder demo

MNIST Autoencoder

Compress and reconstruct digits with an autoencoder architecture.

Screenshot of reinforcement learning demo

Deep Q Learning

Explore reinforcement learning agents using Deep Q-Networks.

Screenshot of neural network image painting demo

Neural Painter

Watch a fully-connected net “paint” an image pixel by pixel.

Screenshot comparing SGD, Adagrad, and Adadelta trainers

Optimizer Playground

Compare SGD, Adagrad, and Adadelta on the same dataset in real time.

Want to dive deeper? Browse the full ConvNetJS intro page or read the detailed documentation.