Awesome
machinelearn.js
machinelearn.js is a Machine Learning library written in Typescript. It solves Machine Learning problems and teaches users how Machine Learning algorithms work.
<img src="https://i.imgur.com/I5VbqB1.jpg">User Installation
Using yarn
$ yarn add machinelearn
Using NPM
$ npm install --save machinelearn
On the browsers
We use jsdeliver to distribute browser version of machinelearn.js
<script src="https://cdn.jsdelivr.net/npm/machinelearn/machinelearn.min.js"></script>
<script>
const { RandomForestClassifier } = ml.ensemble;
const cls = new RandomForestClassifier();
</script>
Please see https://www.jsdelivr.com/package/npm/machinelearn for more details.
Accelerations
By default, machinelearning.js will use pure Javascript version of tfjs. To enable acceleration
through C++ binding or GPU, you must import machinelearn-node
for C++ or machinelearn-gpu
for GPU.
- C++
- installation
yarn add machinelearn-node
- activation
import 'machinelearn-node';
- GPU
- installation
yarn add machinelearn-gpu
- activation
import 'machinelearn-gpu';
Highlights
- Machine Learning on the browser and Node.js
- Learning APIs for users
- Low entry barrier
Development
We welcome new contributors of all level of experience. The development guide will be added to 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 :heart: Machine Learning
Simplicity
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 trainingpredict
for inferencingtoJSON
for saving the model's statefromJSON
for loading the model from the checkpoint
Testing
Testing ensures you that you are currently using the most stable version of machinelearn.js
$ npm run test
Supporting
Simply give us a :star2: by clicking on <img width="45" src="https://i.imgur.com/JEOaKBk.png">
Contributing
We simply follow "fork-and-pull" workflow of Github. Please read CONTRIBUTING.md for more detail.
Further notice
Great references that helped building this project!
- https://machinelearningmastery.com/
- https://github.com/mljs/ml
- http://scikit-learn.org/stable/documentation.html
Contributors
Thanks goes to these wonderful people (emoji key):
<!-- ALL-CONTRIBUTORS-LIST:START - Do not remove or modify this section --> <!-- prettier-ignore -->