https://github.com/machinelearnjs/machinelearn-gpu
machinelearn.js CUDA GPU backend for acceleration
https://github.com/machinelearnjs/machinelearn-gpu
Last synced: 2 months ago
JSON representation
machinelearn.js CUDA GPU backend for acceleration
- Host: GitHub
- URL: https://github.com/machinelearnjs/machinelearn-gpu
- Owner: machinelearnjs
- License: mit
- Created: 2019-01-01T12:07:03.000Z (about 7 years ago)
- Default Branch: master
- Last Pushed: 2019-01-09T11:53:32.000Z (about 7 years ago)
- Last Synced: 2025-10-04T01:56:32.689Z (5 months ago)
- Language: Shell
- Homepage:
- Size: 68.4 KB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# machinelearn-gpu
machinelearn-gpu is a module to enable GPU acceleration for machinelearn.js projects.
[](https://ci.appveyor.com/project/JasonShin/machinelearn-gpu)
[](https://app.fossa.io/projects/git%2Bgithub.com%2FJasonShin%2Fkalimdorjs?ref=badge_shield)
[](https://slack.bri.im)
# User Installation
You must install [machinelearn-node](https://github.com/kalimdorjs/machinelearn-node) first since it is a dependency
```bash
$ yarn add machinelearn-node
```
Using yarn
```bash
$ yarn add machinelearn-gpu
```
Using NPM
```bash
$ npm install --save machinelearn-gpu
```
Then you should require the package in your project
```javascript
require('machinelearn-gpu');
```
Above will enable GPU acceleration provided by [tfjs-node-gpu](https://github.com/tensorflow/tfjs-node)
# 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
# Testing
Testing ensures you that you are currently using the most stable version of Kalimdor.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.