Awesome Open Source
Awesome Open Source

Read our ml5.js Code of Conduct and software licence here!

ml5

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This project is currently in development.

Friendly machine learning for the web!

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.

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.

Please read our Code of Conduct, which establishes our commitment to make ml5.js a friendly and welcoming environment.

Usage

Before getting started with ml5.js, review our Code of Conduct. There are several ways you can use the ml5.js library:

  • You can use the latest version (0.12.2) by adding it to the head section of your HTML document:

v0.12.2

<script src="https://unpkg.com/[email protected]/dist/ml5.min.js" type="text/javascript"></script>
  • If you need to use an earlier version for any reason, you can change the version number. The previous versions of ml5 can be found here. You can use those previous versions by replacing <version> with the ml5 version of interest:
<script src="https://unpkg.com/[email protected]<version>/dist/ml5.min.js" type="text/javascript"></script>

For example:

<script src="https://unpkg.com/[email protected]/dist/ml5.min.js" type="text/javascript"></script>
  • You can also reference "latest", but we do not recommend this as your code may break as we update ml5.
<script src="https://unpkg.com/[email protected]/dist/ml5.min.js" type="text/javascript"></script>

Resources

Standalone Examples

You can find a collection of standalone examples in this repository within the examples/ directory. You can also test working hosted of the examples online on the ml5.js examples index website.

These examples are meant to serve as an introduction to the library and machine learning concepts.

Code of Conduct

We believe in a friendly internet and community as much as we do in building friendly machine learning for the web. Please refer to our Code of Conduct for our rules for interacting with ml5 as a developer, contributor, or as a person using the library.

Contributing

Want to be a contributor to the ml5.js library? If yes and you're interested to submit new features, fix bugs, or help develop the ml5.js ecosystem, please go to our CONTRIBUTING documentation to get started.

See CONTRIBUTING

Acknowledgements

ml5.js is supported by the time and dedication of open source developers from all over the world. Funding and support is generously provided by a Google Education grant at NYU's ITP/IMA program.

Many thanks BrowserStack for providing testing support.

Contributors

Thanks goes to these wonderful people (emoji key):


Daniel Shiffman


Cristbal Valenzuela


Yining Shi


Hannah Davis


Joey Lee


AshleyJaneLewis


Ellen Nickles


Itay Niv


Nikita Huggins


Arnab Chakravarty


Aidan Nelson


WenheLI


Darius Kazemi


Dingsu Wang


garym140


Gene Kogan


Hayley Hwang


Lisa Jamhoury


Alejandro Matamala Ortiz


Maya Man


Mimi Onuoha


Yuuno, Hibiki


Dan Oved


Stephanie Koltun


YG Zhang


Wenqi Li


Brent Bailey


Jonarod


Jasmine Otto


Zaid Alyafeai


Jacob Foster


Memo Akten


Mohamed Amine


Oliver Wright


Marshal Hayes


Reiichiro Nakano


Nikhil Thorat


Irene Alvarado


Andrew Lee


Jerhone


achimkoh


Jim


Junya Ishihara


Naoto HIDA


aarn montoya-moraga


b2renger


Aditya Sharma


okuna291


Jenna


nicoleflloyd


jepster-dk


Xander Jake de los Santos


Cassie Tarakajian


Dave Briccetti


Sblob1


Jared Wilber


danilo


Emma Goodliffe


Yang


Lydia Jessup


CJ R.


Fabio Corona


Tobias Nickel


Michael Salaverry


Rob


Pujaa Rajan


Nick McIntyre


Andy Baio


Wenqi Li


garym140


Jim


Yeswanth


Pettrus Sherlock


danilo


Andreas Refsgaard


Brian Jordan


bradley inniss


Kaushlendra Pratap


maxdevjs


josher19


Frederik De Bleser


Violet


Tirta Wening Rachman


Mik Kruschel


Takanobu Asanuma


Martin L. Jensen


Hugo Romano


Darshan Sen


Ludwig Stumpp


Bomani Oseni McClendon


Jang Haemin


Anton Filatov


Elijah Lucian


Tam


RGV


hansvana


Ali Karpuzoglu


Jacob Wysko


Dilwoar Hussain


Manaswini Das


Benjamin Botwin


Henrique Mota


CaseyPan


Sam Tarakajian


Michael Bell


machenmusik


Pranav Dudhane


Tndi Szsz


hellonun


Pierre Grimaud


Greg French


Dale Markowitz


Ragland Asir


Tom-Lucas Sger


altruios


mennosc


neta


Koji


josephrocca


Lauren Lee McCarthy


Sorin Curescu


mofanke


Ikko Ashimine


Mudasar-Makandar


Amir Feqhi


DasK


Amir


lindapaiste


Evan Weinberg


Coder Gautam


Yong-Yuan Chen


adrianfiedler

This project follows the all-contributors specification. Contributions of any kind welcome!



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