Beginners Guide to Machine Learning in JavaScript - ml5.js: Classifying Drawings with DoodleNet

Quick, draw! In this video, I demonstrate how to use the DoodleNet pre-trained machine learning model to classify drawings of cats, strawberries, and other common doodles in JavaScript (with p5.js and ml5.js). 💻 Code: https://thecodingtrain.com/learning/ml5/9.1-doodlenet.html Links discussed in this video: 🔗 DoodleNet - Model Biography (ml5js.org): https://learn.ml5js.org/#/reference/image-classifier?id=doodlenet-model-biography 🔗 Quick, Draw! The Data: https://quickdraw.withgoogle.com/data 🔗 DoodleNet Repository (GitHub): https://github.com/yining1023/doodleNet Other videos mentioned in this video: 🎥 Quick, Draw! - Coding Challenge #122: https://youtu.be/yLuk0twx8Hc 🎥 Shape Classifier with ml5.js - Coding Challenge #158: https://youtu.be/3MqJzMvHE3E Timestamps: 0:00 Introduction! About DoodleNet 1:35 Code! doodleClassifier 3:24 Try! console logging results 4:31 Code! resultsDiv and loop classification 6:51 Try! drawing a cat 8:17 Code! make it work with video 8:59 Try! draw a strawwwberrrry 9:11 Code! add threshold 9:44 Try! thicker pen 10:26 Try! threshold on/off 10:51 Try! A snowman 11:13 Wrap up! 💖 🚂 Website: http://thecodingtrain.com/ 👾 Share Your Creation! https://thecodingtrain.com/Guides/community-contribution-guide.html 🚩 Suggest Topics: https://github.com/CodingTrain/Rainbow-Topics 💡 GitHub: https://github.com/CodingTrain 💬 Discord: https://discord.gg/hPuGy2g 💖 Membership: http://youtube.com/thecodingtrain/join 🛒 Store: https://standard.tv/codingtrain 📚 Books: https://www.amazon.com/shop/thecodingtrain 🖋️ Twitter: https://twitter.com/thecodingtrain 📸 Instagram: https://www.instagram.com/the.coding.train/ 🎥 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 🔗 p5.js Web Editor: https://editor.p5js.org/ 🔗 Processing: https://processing.org 📄 Code of Conduct: https://github.com/CodingTrain/Code-of-Conduct