Download
ConvNetJS is a Javascript library for training Deep Learning models (Neural Networks) entirely in your browser. Open a tab and you're training. No software requirements, no compilers, no installations, no GPUs, no sweat. ConvNetJS is an implementation of Neural networks, together with nice browser-based demos. It currently supports common Neural Network modules (fully connected layers, non-linearities), classification (SVM/Softmax) and Regression (L2) cost functions, ability to specify and train Convolutional Networks that process images, and experimental Reinforcement Learning modules, based on Deep Q Learning. The library allows you to formulate and solve Neural Networks in Javascript. If you would like to add features to the library, you will have to change the code in src/ and then compile the library into the build/ directory. The compilation script simply concatenates files in src/ and then minifies the result.
Features
- You can define a 2-layer neural network and train it on a single data point
- You can formulate and solve Neural Networks in Javascript
- You can train Convolutional Neural Network if you wish to predict on images
- There are two ways to use the library, inside the browser, or on a server using node.js.
- Train a Convolutional Neural Network on the MNIST digits dataset in your browser
- The dataset is fairly easy and one should expect to get somewhere around 99% accuracy
Project Samples
