This project is currently in development.
ml5.js aims to make machine learning approachable for a broad audience of artists, creative coders, and students. The library provides access to machine learning algorithms and models in the browser, building on top of TensorFlow.js with no other external dependencies.
The library is supported by code examples, tutorials, and sample data sets with an emphasis on ethical computing. Bias in data, stereotypical harms, and responsible crowdsourcing are part of the documentation around data collection and usage.
ml5.js is heavily inspired by Processing and p5.js.
There are several ways you can use the ml5.js library:
- You can use the latest online version by adding it to the head section of your HTML document:
<script src="https://unpkg.com/ml5@latest/dist/ml5.min.js" type="text/javascript"></script>- Or you can use an specific version of the library: v0.2.1
<script src="https://unpkg.com/ml5@0.2.1/dist/ml5.min.js" type="text/javascript"></script>v0.1.3
<script src="https://unpkg.com/ml5@0.1.3/dist/ml5.min.js" type="text/javascript"></script>- Or you can download the minified and include the file:
<script src="ml5.min.js" type="text/javascript"></script>You can find a collection of standalone examples in this repository: github.com/ml5js/ml5-examples
These examples are meant to serve as an introduction to the library and machine learning concepts.
See CONTRIBUTING
Thanks BrowserStack for providing testing support.