In this video, I discuss the backpropagation algorithm as it relates to supervised learning and neural networks. Code: https://thecodingtrain.com/tracks/neural-networks/neural-networks/14-backpropagation-part-1
💻 Github Repo: https://github.com/CodingTrain/Toy-Neural-Network-JS
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References:
🔗 Intelligence and Learning: https://github.com/nature-of-code/NOC-S17-2-Intelligence-Learning/tree/master/week4-neural-networks
🔗 Make Your Own Neural Network: https://www.amazon.com/Make-Your-Own-Neural-Network-ebook/dp/B01EER4Z4G
🔗 Tensorflow.js: https://github.com/nature-of-code/NOC-S17-2-Intelligence-Learning/tree/master/week4-neural-networks
🔗 Sigmoid function: https://en.wikipedia.org/wiki/Sigmoid_function
Videos:
🔗
https://www.youtube.com/watch?v=jc2IthslyzM
🔗 https://www.youtube.com/playlist?list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab
🔗 https://www.youtube.com/playlist?list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi
🔗
https://www.youtube.com/watch?v=IHZwWFHWa-w
Timestamps:
0:00 Introduction
0:33 Supervised learning
1:21 Key terminology
3:18 Resources
4:40 The backpropagation algorithm
7:54 Apportioning the error
19:18 Outro
Editing by Mathieu Blanchette
Animations by Jason Heglund
Music from Epidemic Sound
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#neuralnetwork #backpropagation #javascript