Welcome to the ml5.js project! ml5.js is an open source library with a goal of making machine learning approachable for a broad audience of artists, creative coders, and students. Drawing inspiration from Processing and p5.js, ml5.js aims to bridge the gap between the technical complexity of machine learning and the creativity of beginners and artists. The library provides access to machine learning algorithms and models in the browser, building on top of TensorFlow.js.
The project began as a collaborative effort at NYU's ITP program, involving contributions from students, researchers, faculty, and alumni. Inspired by the p5.js project's focus on making coding accessible and inclusive, ml5.js aims to expand this mission to the domain of machine learning. Initial work on the project was supported by a Google Research Award, which helped to formalize the relationship between TensorFlow.js and ml5.js.
A key feature of ml5.js is its ability to run pretrained models for interaction. These models can classify images, identify body poses, recognize facial landmarks, hand positions, and more. You can use these models as they are, or as a starting point for further learning along with ml5.js's neural network module which enables training your own models.
The ml5.js library comes with code examples and educational materials with a goal of emphasizing ethical computing and opening the door for discussion on bias in data and machine learning. We're dedicated to building user-friendly machine learning for the web, and we're glad you're here!
ml5.js is heavily inspired by the work of The Processing Foundation. Learn more about the history and origins of the ml5.js project in the ITP Adjacent article and on medium.com/@ml5js.
ml5.js is a community interested in exploring and empowering the creative and ethical application of machine learning. This Code of Conduct is intended to foster a community that is open to anyone interested in joining that exploration.
We are a community of, and in solidarity with, people from every gender identity and expression, sexual orientation, race, ethnicity, size, ability, class, religion, culture, age, skill level, occupation, and background. We acknowledge that not everyone has the time, financial means, or capacity to actively participate, but we recognize and encourage involvement of all kinds. We facilitate and foster access and empowerment. We are all learners.
We accept the claim that technology is a reflection of society, its histories, and its politics. We reject the claim that any technology is neutral and acknowledge that every technology has the potential to do as much harm as good. We acknowledge that when technologies cause harm, the harm disproportionately affects Black/Indigenous, People of Color (BIPOC) queer, trans, disabled, femme, low-income, survivors, and all other marginalized bodies and communities. With this understanding, we work to intentionally engage these groups when hosting, participating in, or developing events (e.g. workshops or meetings), materials (e.g. courses, syllabi, resources), and software (e.g. the ml5.js library, examples, and related and supporting code).
As part of the ml5.js Code of Conduct, we pledge to design, build, and use ml5.js in a way that centers the aforementioned marginalized bodies and communities first, striving to always confront our biases, privileges, and ignorances for our own good and society at large.
Link to the full ml5 code of conduct
Read more about the development of the ml5 code of conduct and software license
ml5.js is supported by the time and dedication of open source developers from all over the world. We are artists, designers, technologists, researchers, educators, students, scientists, developers, parents, children, and everything in-between. We are proud of our growing list of contributors.
The design and development of ml5.js is currently organized via a joint collaboration between ITP/IMA at Tisch School of the Arts and the IMA program at NYU Shanghai. Development is supported in part by a grant by the Shanghai Frontiers Science Center of Artificial Intelligence and Deep Learning.
Initial funding for this project was provided by a 2018 Google Research Award grant at ITP/IMAprogram.
Website design and development is by J.H. Moon, Quinn Fangqing He, Alan Ren, Apoorva Avadhana, Jo Heun Lee, Miaoye Que, Myrah Sarwar, Ozioma Chukwukeme, and Pacey Xiaozao Wang, and supported by Gottfried Haider, Peter Ziyuan Lin, and Dan Shiffman.
The website is based on the original ml5.js website which was designed with ❤ by Milan Gary, Nicole Lloyd, and Arnab Chakravarty and developed by Wenqi Li, Joey Lee, and Dan Shiffman.