ml5 library

Friendly machine learning for the web! πŸ€–

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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/ml5@<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 β€œlatest”, but we do not recommend this as your code may break as we update ml5.
<script src="https://unpkg.com/ml5@latest/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 πŸ— 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 πŸ› 

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

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CristΓ³bal Valenzuela

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Yining Shi

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Hannah Davis

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Joey Lee

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AshleyJaneLewis

πŸ“ 🎨 πŸ“‹ πŸ–‹

Ellen Nickles

πŸ“ πŸ–‹ πŸ€” βœ…

Itay Niv

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Nikita Huggins

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Arnab Chakravarty

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Aidan Nelson

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WenheLI

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Darius Kazemi

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Dingsu Wang

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garym140

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Gene Kogan

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Hayley Hwang

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Lisa Jamhoury

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Alejandro Matamala Ortiz

🎨 πŸ–‹ πŸ“

Maya Man

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Mimi Onuoha

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Yuuno, Hibiki

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Dan Oved

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Stephanie Koltun

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YG Zhang

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Wenqi Li

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Brent Bailey

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Jonarod

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Jasmine Otto

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Zaid Alyafeai

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Jacob Foster

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Memo Akten

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Mohamed Amine

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Oliver Wright

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Marshal Hayes

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Reiichiro Nakano

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Nikhil Thorat

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Irene Alvarado

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Andrew Lee

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Jerhone

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achimkoh

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Jim

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Junya Ishihara

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Naoto HIÉDA

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aarΓ³n montoya-moraga

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b2renger

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Aditya Sharma

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okuna291

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Jenna

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nicoleflloyd

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jepster-dk

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Xander Jake de los Santos

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Cassie Tarakajian

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Dave Briccetti

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Sblob1

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Jared Wilber

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danilo

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Emma Goodliffe

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Yang

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Lydia Jessup

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CJ R.

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Fabio Corona

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Tobias Nickel

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Michael Salaverry

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Rob

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Pujaa Rajan

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Nick McIntyre

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Andy Baio

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Wenqi Li

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garym140

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Jim

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Yeswanth

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Pettrus Sherlock

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danilo

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Andreas Refsgaard

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Brian Jordan

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bradley inniss

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Kaushlendra Pratap

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maxdevjs

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josher19

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Frederik De Bleser

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Violet

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Tirta Wening Rachman

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MikΓ‘ Kruschel

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Takanobu Asanuma

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Martin L. Jensen

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Hugo Romano

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Darshan Sen

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Ludwig Stumpp

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Bomani Oseni McClendon

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Jang Haemin

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Anton Filatov

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Elijah Lucian

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Tam

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RGV

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hansvana

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Ali Karpuzoglu

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Jacob Wysko

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Dilwoar Hussain

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Manaswini Das

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Benjamin Botwin

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Henrique Mota

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CaseyPan

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Sam Tarakajian

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Michael Bell

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machenmusik

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Pranav Dudhane

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TΓΌndi SzΓ‘sz

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hellonun

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Pierre Grimaud

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Greg French

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Dale Markowitz

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Ragland Asir

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Tom-Lucas SΓ€ger

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altruios

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mennosc

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neta

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Koji

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Lauren Lee McCarthy

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Sorin Curescu

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Ikko Ashimine

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Amir Feqhi

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DasK

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Amir

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lindapaiste

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Evan Weinberg

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Coder Gautam

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Yong-Yuan Chen

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adrianfiedler

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