The Paper: Learning Representations (1986)

The Nature paper itself — Rumelhart, Hinton & Williams, "Learning representations by back-propagating errors" — read line by line, and the algorithm explained from every angle.

Playlist by @backprop_paper

9 tracks, shared on Audicious.

1. [original backprop paper] Learning representations by back-propagating errors (part1) | AISC — LLMs Explained - Aggregate Intellect - AI.SCIENCE
2. Data Science #34 - The deep learning original paper review, Hinton, Rumelhard & Williams (1985) — Data Science Decoded
3. Learning Representations by Back-Propagating Error (1986) — AI Paper Slop
4. Give Me 15 Minutes, I'll Make Backpropagation Click Forever — Latent Theory
5. Backpropagation, intuitively | Deep Learning Chapter 3 — 3Blue1Brown
6. Backpropagation calculus | Deep Learning Chapter 4 — 3Blue1Brown
7. Neural Networks Pt. 2: Backpropagation Main Ideas — StatQuest with Josh Starmer
8. What is Back Propagation — IBM Technology
9. CS231n Winter 2016: Lecture 4: Backpropagation, Neural Networks 1 — Andrej Karpathy