Backpropagation

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Papers

Learning Representations by Back-propagating Errors

  • The famous paper introducing backpropagation for machine learning

Lectures

Backpropagation Lecture

  • Andrej Karpathy’s lecture on backpropagtion


Lecture 6: Backpropagation

  • A University of Michigan lecture on backprop by Justin Johnson


Lecture 4: Backpropagation and Neural Networks

  • A Stanford Lecture on backprop by Serena Yeung

Videos

3Blue1Brown on Backpropagation Part 1 and Part 2

  • A couple videos explaining backpropagation and the underlying math

  • While you’re at it, check out the rest of his videos on neural networks


Gradient Descent for Neural Networks and Backpropagation Intuition

  • Andrew Ng’s walkthrough of backpropagation from his Coursera course

Posts

Yes, You Should Understand Backprop

  • A medium post by Andrej Karpathy about why learning backprop is still important


Backpropagation Intution

  • A lesson on backpropagation from Karpathy’s Stanford course


Backpropagation | Brilliant

  • A brilliant (pun intended), detailed lesson on backprop by Brilliant.org


Backpropagation | ML Glossary

  • A review of the chain rule, backpropagation, and some code

Code Examples

Pytorch Example

  • A simple example of training a neural network in pytorch using backpropagation


Neural Network backpropagation from scratch in Python

  • A cool example of training a neural network from scratch with just numpy

Tagged Pages: Neural Networks (MLPs)

Know a great resource on Backpropagation? Send it to us at contactbackprop@gmail.com!