Lecture 2.3: Backpropagation, a tensor view (DLVU)

lecturer: Peter Bloem
course website: dlvu.github.io
In this video, we work out the backpropagation algorithm in a vectorized version: that is purely in terms of basic linear algebra operations like matrix and vector multiplication. This helps us to express neural networks in a clean notation, and to accelarate their computation.

[@ron0studios]

extremely underrated resource for learning backpropagation! Thank you for this!

[@antonispolykratis3283]

This is a great course. Thanks for all these details!

[@vesk4000]

This is exceptionally well explained. I'm a student at TU Delft and this really helped me understand how to speed up my code, and why it works. Thanks a lot!