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machinelearn.js is a Machine Learning library written in Typescript. It solves Machine Learning problemsand teaches users how Machine Learning algorithms work.

Using yarn

$ yarn add machinelearn

Using NPM

$ npm install --save machinelearn

By default, machinelearning.js will use pure Javascript version of tfjs. To enable accelerationthrough C++ binding or GPU, you must importmachinelearn-node for C++ ormachinelearn-gpu for GPU.

1. C++

• installation

yarn add machinelearn-node

• activation

import'machinelearn-node';

2. GPU

• installation

yarn add machinelearn-gpu

• activation

import'machinelearn-gpu';

• Machine Learning on the browser and Node.js
• Learning APIs for users
• Low entry barrier

We welcome new contributors of all level of experience. The development guide will be addedto assist new contributors to easily join the project.

• You want to participate in a Machine Learning project, which will boost your Machine Learning skills and knowledge
• Looking to be part of a growing community
• You want to learn Machine Learning
• You like Typescript ❤️ Machine Learning

machinelearn.js provides a simple and consistent set of APIs to interact with the models and algorithms.For example, all models have follow APIs:

• fit for training
• predict for inferencing
• toJSON for saving the model's state
• fromJSON for loading the model from the checkpoint

Testing ensures you that you are currently using the most stable version of machinelearn.js

$ npm runtest

Simply give us a 🌟 by clicking on

We simply follow "fork-and-pull" workflow of Github. Please read CONTRIBUTING.md for more detail.

Great references that helped building this project!

• https://machinelearningmastery.com/
• https://github.com/mljs/ml
• http://scikit-learn.org/stable/documentation.html

Thanks goes to these wonderful people (emoji key):

Jason Shin 📝🐛💻📖⚠️	Jaivarsan 💬🤔📢	Oleg Stotsky 🐛💻📖⚠️	Ben 💬🎨📢🐛💻	Christoph Reinbothe 💻🤔🚇👀	Adam King 💻⚠️📖