Open Source TypeScript Neural Network Libraries

SponsorBlock is an open-source crowdsourced browser extension and open API for skipping sponsor segments in YouTube videos. Users submit when a sponsor happens from the extension, and the extension automatically skips sponsors it knows about using a privacy-preserving query system. It also supports skipping other categories, such as intros, outros, and reminders to subscribe, and skipping to the point with highlights. The extension also features an upvote/downvote system with a weighted random-based distribution algorithm. Once one person submits this information, everyone else with this extension will skip right over the sponsored segment. SponsorBlock is a crowdsourced browser extension that let's anyone submit the start and end time's of sponsored segments of YouTube videos.

GPU accelerated Neural networks in JavaScript for Browsers and Node.js. brain.js is a GPU accelerated library for Neural Networks written in JavaScript. Brain.js depends on a native module headless-go for GPU support. In most cases installing brain.js from npm should just work. However, if you run into problems, this means prebuilt binaries are not able to download from GitHub repositories and you might need to build it yourself. Brain.js is super simple to use. You do not need to know Neural Networks in detail to work with this. Brain.js performs computations using GPU and gracefully fallback to pure JavaScript when GPU is not available. Brain.js provides multiple neural network implementations as different neural nets can be trained to do different things well. Easily export and import trained models using JSON format or as a function. Host pre-trained models on your website easily.

TensorFlow.js is a library for machine learning in JavaScript. Develop ML models in JavaScript, and use ML directly in the browser or in Node.js. Use off-the-shelf JavaScript models or convert Python TensorFlow models to run in the browser or under Node.js. Retrain pre-existing ML models using your own data. Build and train models directly in JavaScript using flexible and intuitive APIs. Tensors are the core datastructure of TensorFlow.js They are a generalization of vectors and matrices to potentially higher dimensions. Built on top of TensorFlow.js, the ml5.js library provides access to machine learning algorithms and models in the browser with a concise, approachable API. Comfortable with concepts like Tensors, Layers, Optimizers and Loss Functions (or willing to get comfortable with them)? TensorFlow.js provides flexible building blocks for neural network programming in JavaScript.