MIT Introduction to Deep Learning 6.S191: Lecture 2
Recurrent Neural Networks
Lecturer: Ava Amini
** New 2024 Edition **

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Lecture Outline
0:00​ Introduction
3:42​ Sequence modeling
5:30​ Neurons with recurrence
12:20 Recurrent neural networks
14:08 RNN intuition
17:14​ Unfolding RNNs
19:54 RNNs from scratch
22:41 Design criteria for sequential modeling
24:24 Word prediction example
31:50​ Backpropagation through time
33:40 Gradient issues
37:15​ Long short term memory (LSTM)
40:00​ RNN applications
44:00 Attention fundamentals
46:46 Intuition of attention
49:13 Attention and search relationship
51:22 Learning attention with neural networks
57:45 Scaling attention and applications
1:00:08 Summary
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