MIT Introduction to Deep Learning 6.S191: Lecture 2
Recurrent Neural Networks
Lecturer: Ava Soleimany
January 2021
For all lectures, slides, and lab materials: http://introtodeeplearning.com
Lecture Outline
0:00 - Introduction
2:37 - Sequence modeling
4:54 - Neurons with recurrence
12:07 - Recurrent neural networks
14:13 - RNN intuition
17:01 - Unfolding RNNs
18:39 - RNNs from scratch
22:12 - Design criteria for sequential modelling
23:37 - Word prediction example
31:31 - Backpropagation through time
33:40 - Gradient issues
38:46 - Long short term memory (LSTM)
47:47 - RNN applications
52:15 - Attention
59:24 - Summary
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