Coding Challenge #92: XOR Problem

From the creator

In this coding challenge, I use my Toy Neural Networks library to solve the XOR problem. Code: https://thecodingtrain.com/challenges/92-xor-problem 🕹️ p5.js Web Editor Sketch: https://editor.p5js.org/codingtrain/sketches/_QGR5d0Bi 🎥 Previous video: https://youtu.be/JrRO3OnWs5s?list=PLRqwX-V7Uu6ZiZxtDDRCi6uhfTH4FilpH 🎥 Next video: https://youtu.be/uWzPe_S-RVE?list=PLRqwX-V7Uu6ZiZxtDDRCi6uhfTH4FilpH 🎥 All videos: https://www.youtube.com/playlist?list=PLRqwX-V7Uu6ZiZxtDDRCi6uhfTH4FilpH References: 💻 Toy-Neural-Network-JS: https://github.com/CodingTrain/Toy-Neural-Network-JS 💻 Deeplearn.js: https://deeplearnjs.org 💻 ml5.js: https://ml5js.org/ Videos: 🚂 My Neural Networks series: https://www.youtube.com/playlist?list=PLRqwX-V7Uu6aCibgK1PTWWu9by6XFdCfh 🚂 My Perceptron video: https://codingtrain.github.io/website-archive/more/archive/nature-of-code/10-Neural-Networks/10.2-Neural-Networks-Perceptron-Part-1 🎥 Neural Networks: https://www.youtube.com/playlist?list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi Live Stream Archive: 🔴 Live Stream Archive #118: https://youtu.be/e8H588SXu6U?t=8090s 🔴 Live Stream Archive #119: https://youtu.be/f9vaiHoq-Fk?t=3171s Timestamps: 0:00 Introduction 1:15 Machine learning 3:00 Supervised learning 4:20 XOR problem 7:07 Hidden layer 11:49 Training data 13:14 nn.train() 15:14 nn.predict() 16:26 Visualize results 19:30 Initializing weights 20:15 Learning rate 22:33 Add more hidden nodes 23:40 What's next? Editing by Mathieu Blanchette Animations by Jason He

Published 2018-02-12 · Watch on YouTube ↗
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