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https://github.com/machinelearnjs/machinelearnjs
Machine Learning library for the web and Node.
https://github.com/machinelearnjs/machinelearnjs
data-preprocessing easy-to-use feature-extraction machine-learning minimalistic node probabilistic-models random-forest statistical-learning structured-data svm web
Last synced: 3 months ago
JSON representation
Machine Learning library for the web and Node.
- Host: GitHub
- URL: https://github.com/machinelearnjs/machinelearnjs
- Owner: machinelearnjs
- License: mit
- Created: 2018-04-29T00:14:06.000Z (almost 7 years ago)
- Default Branch: master
- Last Pushed: 2022-12-08T18:33:02.000Z (about 2 years ago)
- Last Synced: 2024-04-24T02:05:34.370Z (10 months ago)
- Topics: data-preprocessing, easy-to-use, feature-extraction, machine-learning, minimalistic, node, probabilistic-models, random-forest, statistical-learning, structured-data, svm, web
- Language: TypeScript
- Homepage: https://www.machinelearnjs.com/
- Size: 4.26 MB
- Stars: 537
- Watchers: 15
- Forks: 54
- Open Issues: 52
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
Awesome Lists containing this project
README
# 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.
[](https://dev.azure.com/jasonShin91/machinelearn.js/_build/latest?definitionId=1&branchName=master)
[](https://ci.appveyor.com/project/JasonShin/machinelearnjs/branch/master)
[](https://app.fossa.io/projects/git%2Bgithub.com%2FJasonShin%2Fkalimdorjs?ref=badge_shield)
[](https://slack.bri.im)
[](https://app.zenhub.com/workspaces/machinelearnjs-5bef95354b5806bc2bf57ff3/boards?repos=131453423)
# User Installation
Using yarn
```bash
$ yarn add machinelearn
```
Using NPM
```bash
$ npm install --save machinelearn
```
On the browsers
We use [jsdeliver](https://www.jsdelivr.com/package/npm/machinelearn) to distribute browser version of machinelearn.js
```html
const { RandomForestClassifier } = ml.ensemble;
const cls = new RandomForestClassifier();
```
Please see [https://www.jsdelivr.com/package/npm/machinelearn](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.
1. C++
* installation
```bash
yarn add machinelearn-node
```
* activation
```javascript
import 'machinelearn-node';
```
2. GPU
* installation
```bash
yarn add machinelearn-gpu
```
* activation
```javascript
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 training
* `predict` for inferencing
* `toJSON` for saving the model's state
* `fromJSON` for loading the model from the checkpoint
# Testing
Testing ensures you that you are currently using the most stable version of machinelearn.js
```bash
$ npm run test
```
# Supporting
Simply give us a :star2: by clicking on 
# 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](https://github.com/kentcdodds/all-contributors#emoji-key)):
| [
Jason Shin](https://github.com/JasonShin)
[📝](#blog-JasonShin "Blogposts") [🐛](https://github.com/machinelearnjs/machinelearnjs/issues?q=author%3AJasonShin "Bug reports") [💻](https://github.com/machinelearnjs/machinelearnjs/commits?author=JasonShin "Code") [📖](https://github.com/machinelearnjs/machinelearnjs/commits?author=JasonShin "Documentation") [⚠️](https://github.com/machinelearnjs/machinelearnjs/commits?author=JasonShin "Tests") | [
Jaivarsan](https://github.com/greed2411)
[💬](#question-greed2411 "Answering Questions") [🤔](#ideas-greed2411 "Ideas, Planning, & Feedback") [📢](#talk-greed2411 "Talks") | [
Oleg Stotsky](https://github.com/OlegStotsky)
[🐛](https://github.com/machinelearnjs/machinelearnjs/issues?q=author%3AOlegStotsky "Bug reports") [💻](https://github.com/machinelearnjs/machinelearnjs/commits?author=OlegStotsky "Code") [📖](https://github.com/machinelearnjs/machinelearnjs/commits?author=OlegStotsky "Documentation") [⚠️](https://github.com/machinelearnjs/machinelearnjs/commits?author=OlegStotsky "Tests") | [
Ben](https://github.com/benjaminmcdonald)
[💬](#question-benjaminmcdonald "Answering Questions") [🎨](#design-benjaminmcdonald "Design") [📢](#talk-benjaminmcdonald "Talks") [🐛](https://github.com/machinelearnjs/machinelearnjs/issues?q=author%3Abenjaminmcdonald "Bug reports") [💻](https://github.com/machinelearnjs/machinelearnjs/commits?author=benjaminmcdonald "Code") | [
Christoph Reinbothe](https://github.com/LSBOSS)
[💻](https://github.com/machinelearnjs/machinelearnjs/commits?author=LSBOSS "Code") [🤔](#ideas-LSBOSS "Ideas, Planning, & Feedback") [🚇](#infra-LSBOSS "Infrastructure (Hosting, Build-Tools, etc)") [👀](#review-LSBOSS "Reviewed Pull Requests") | [
Adam King](https://github.com/adamjking3)
[💻](https://github.com/machinelearnjs/machinelearnjs/commits?author=adamjking3 "Code") [⚠️](https://github.com/machinelearnjs/machinelearnjs/commits?author=adamjking3 "Tests") [📖](https://github.com/machinelearnjs/machinelearnjs/commits?author=adamjking3 "Documentation") |
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