Stanford University · YouTube
AI Luminaries
A curated collection of videos featuring top experts in artificial intelligence.
This live stream is a continuation of neural network series. I attempt to discuss backpropagation, but it mostly goes haywire.
Timestamps:
30:20 - Reading Random Numbers
36:22 - Backpropagation Part 1
1:06:56 - Backpropagation Part 2
1:40:25 - Learning with Gradient Descent
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🎥 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
References:
SFPC's Learning to Teach 2018: https://medium.com/@sfpc/learning-to-teach-2018-4dca068b0fb8
Michael Nielsen's Book on Neural Networks: http://neuralnetworksanddeeplearning.com/
Deeplearn.js: https://deeplearnjs.org/
Sigmoid function on Wikipedia: https://en.wikipedia.org/wiki/Sigmoid_function
Videos:
My Neural Networks series: https://www.youtube.com/playlist?list=PLRqwX-V7Uu6aCibgK1PTWWu9by6XFdCfh
3Blue1Brown Neural Networks playlist: https://www.youtube.com/playlist?list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi
3Blue1Brown's Linear Algebra playlist: https://www.youtube.com/playlist?list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab
Gradient Descent by 3Blue1Brown: https://youtu.be/IHZwWFHWa-w
Gradient Descent by Siraj Raval: https://youtu.be/XdM6ER7zTLk
My Video on Gradient Descent: https://youtu.be/jc2IthslyzM
Source Code for the all Video Lessons: https://github.com/CodingTrain/Rainbow-Code
📄 Code of Conduct: https://github.com/CodingTrain/Code-of-Conduct
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Stanford University · YouTube
A curated collection of videos featuring top experts in artificial intelligence.
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