The ml5.js community page is dedicated to highlighting artists, technologists, makers, activists, thinkers, tinkerers, researchers, scientists, designers, students, and anyone/everyone who are working in and around machine learning in thoughtful ways. Many of these posts not only showcase what is possible with ml5.js but also what can be done when applying machine learning methodologies and technologies more broadly. Special emphasis is given to projects that highlight ethical and critical engagement with technology and/or are simply delightful.
Coming soon!
In this tutorial i have shown you how to create AI Image classification using machine learning.
In this video, I use the "pre-trained" MobileNet model to classify the content of an image.
A robotic car with an hm-10 ble module that is controlled by human poses detected in real-time using p5.js and the posenet library. A neural network is trained to recognize 5 different poses and these poses are used to control the car over Bluetooth.
I show how I combined ml5 PoseNet (machine learning body pose identification) with p5play (physics and game engine) using p5.js.
This playlist demonstrates how to use ml5.js for web-based machine learning as well as showcasing how you can combine it with other libraries like p5.js for creative coding and matter.js for physics simulations. Each tutorial is designed to be very interactive and fun, guiding you through exciting projects that show how these tools can work together seamlessly to bring your creative ideas to life.
If you are interested to share your work, highlight an interesting article/video, or get in touch, we'd love to hear from you!