“ Wait, what?? That’s a horrible idea! “
During the past year our team is building Bit which makes it simpler to build software using components. As part of our work, we develop ML and NLP algorithms to better understand how code is written, organized and used.
This library provides fast neuro-evolution & backpropagation for the browser and Node.js, with a few built-in networks including perceptron, LSTM, GRU, Nark and more. Here is a rookie tutorial for simple training.
This popular library allows you to train neural networks in a browser or run pre-trained models in inference mode, and even claims it can be used as NumPy for the web. With an easy-to-pick-up API this library can be used for a verity for useful applications, and is actively maintained.
Deep playground is an interactive visualization of neural networks, written in TypeScript using d3.js. Although this project basically contains a very basic playground for tensorflow, it can be repurposed for different means or used as a very impressive educational feature for different purposes.
A flexible neural network library for Node.js and the browser, which basically learns to make predictions, using a matrix implementation to process training data and enabling configurable network topology. You can also plug-and-play “minds” which already learned, which can be useful for your apps.
An actively maintained library for Node.js which provides tokenizing, stemming (reducing a word to a not-necessarily morphological root), classification, phonetics, tf-idf, WordNet, string similarity, and more.
Apache MXNet is a deep learning framework that allows you to mix symbolic and imperative programming on the fly with a graph optimization layer for performance. MXnet.js brings a deep learning inference API to the browser.
This library runs Keras models in the browser, with GPU support using WebGL. since Keras uses a number of frameworks as backends, the models can be trained in TensorFlow, CNTK, and other frameworks as well.
A development environment for deep learning that enables you to quickly design neural network architectures and machine learning pipelines with built-in version control for experiment reproduction. Worth checking out.
Not even as much of a library as a very cool demo / web game based on a chrome experiment by Google. Although I’m not sure what to do with it, it’s guaranteed to become the most enjoyable 15 minutes of your day.