Top Node.js Libraries and Tools For Machine Learning
This library is a collection of tools developed by the mljs organization. It include a vast list of libraries under different categories such as unsupervised learning, supervised learning, artificial neural networks, regression, optimization, statistics, data processing and math utilities. Most of these libraries that are included in ml.js are tend ot be used in web browser but if you are looking to work with them in Node.js environment, you will find an npm package.
trainAsync() and support for streams as well.
It is a machine learning framework for Node.js that supports Binary classification, multi-label classification, feature engineering, online learning and real-time classification. It is currently in alpha state and looking for contributors.
It is similar to Tensorflow.js in many ways. One of the similarities is that Keras has support for high-level APIs that take care of abstraction provided by backend frameworks. Using Keras, models can be trained in any backend and you can even hook Tensorflow for that. To Keras with Node.js, there is one limitation you will have to take care. With Node.js, the models only run in CPU mode.
Another flexible neural network library for Node.js, it uses matrix implementation to process training data. It does allow you to configure the network topology and use community made plugins. These plugins generally provide a way to configure pre-trained networks that can go straight to making predictions.
Natural is a library that provides tokenzing, stemming, classification, phonetics, tf-idf, WordNet, and string similarity. In other words, this library provide language facilities that you can use a module in Node.js. This is an interesting project with a variety of use cases.
Another natural language processing that is only
230kb minified when used in the browser. This library provides lot of utilities that are basic and effortless, as well as support community made plugins to extend and use pre-configuration that allow adding vocabulary, fixing errors, and setting context quickly.