Beginner's Guide to Machine Learning in JavaScript with ml5.js

This playlist provides an introduction to developing creative coding projects with machine learning. The theory and application of machine learning algorithms is demonstrated in JavaScript using the p5.js and ml5.js libraries. Learning Objectives: * Develop an intuition for and high level understanding of core machine learning concepts and algorithms, including supervised learning, unsupervised learning, reinforcement learning, transfer learning, classification, and regression. * Be able to apply machine learning algorithms to real-time interaction in media art projects using pre-trained models and “transfer learning” in JavaScript and related tools. * Learn how to collect a custom dataset to train a machine learning model and * Understand how to use a machine learning model to generate media: words, sound, and images. 🔗 ml5.js: https://ml5js.org 🔗 Related Syllabus: https://github.com/ml5js/Intro-ML-Arts-IMA 🔗 p5.js: https://p5js.org 🎥Intro to Programming using p5.js: https://www.youtube.com/playlist?list=PLRqwX-V7Uu6Zy51Q-x9tMWIv9cueOFTFA 📄 Code of Conduct: https://github.com/CodingTrain/Code-of-Conduct 👾Share your contributions: https://thecodingtrain.com/Guides/community-contribution-guide.html 🚂 Website: http://thecodingtrain.com/ 💖 Patreon: https://patreon.com/codingtrain 🛒 Store: https://www.designbyhumans.com/shop/codingtrain/ 📚 Books: https://www.amazon.com/shop/thecodingtrain 🎥 Coding Challenges: https://www.youtube.com/playlist?list=PLRqwX-V7Uu6ZiZxtDDRCi6uhfTH4FilpH 🎥 Intro to Programming: https://www.youtube.com/playlist?list=PLRqwX-V7Uu6Zy51Q-x9tMWIv9cueOFTFA 🔗 p5.js: https://p5js.org 🔗 Processing: https://processing.org