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Shortform link: https://shortform.com/artem In this video we will talk about backpropagation – an algorithm powering the entire field of machine learning and try to derive it from first principles. OUTLINE: 00:00 Introduction 01:28 Historical background 02:50 Curve Fitting problem 06:26 Random vs guided adjustments 09:43 Derivatives 14:34 Gradient Descent 16:23 Higher dimensions 21:36 Chain Rule Intuition 27:01 Computational Graph and Autodiff 36:24 Summary 38:16 Shortform 39:20 Outro USEFUL RESOURCES: Andrej Karpathy’s playlist:    • Neural Networks: Zero to Hero   Jürgen Schmidhuber’s blog on the history of backprop: https://people.idsia.ch/~juergen/who-… CREDITS: Icons by https://www.freepik.com/