MIT 6.S191 (2021): Recurrent Neural Networks

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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