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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