RNN/Sequence Concepts (LSTM/GRU, Masking, Embeddings) Recurrent Neural Networks (RNNs), Clearly Explained!!! (StatQuest with Josh Starmer) Watch: https://www.youtube.com/watch?v=AsNTP8Kwu80 (16:37)
Notes
RNN anatomy, running sequences through the net, shared weights, vanishing/exploding gradients (motivation for LSTM/GRU). Lesson pairs this with padding/masking + embedding examples in the drill. NOTE: 16:37 runs just over the 15-min target but inside the 30-min cap; kept for breadth.
Key moments
0:00 Intro; 4:13 RNN anatomy; 5:59 Running data; 10:31 Shared weights; 11:23 Vanishing/exploding gradients.