Uploaded February 2020 | Updated September 2026, 2 weeks ago
MIT Introduction to Deep Learning 6.S191: Lecture 2
Recurrent Neural Networks
Lecturer: Ava Soleimany
January 2020
For all lectures, slides, and lab materials: introtodeeplearning.com
Lecture Outline
0:00 - Introduction
2:39 - Sequence modeling
9:57 - Recurrent neural networks
14:04 - RNN intuition
16:48 - Unfolding RNNs
20:31 - Backpropagation through time
24:32 - Gradient issues
28:57 - Long short term memory (LSTM)
37:36 - RNN applications
41:30 - Attention
44:05 - Summary
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MIT Introduction to Deep Learning 6.S191: Lecture 2
Recurrent Neural Networks
Lecturer: Ava Soleimany
January 2020
For all lectures, slides, and lab materials: introtodeeplearning.com
Lecture Outline
0:00 - Introduction
2:39 - Sequence modeling
9:57 - Recurrent neural networks
14:04 - RNN intuition
16:48 - Unfolding RNNs
20:31 - Backpropagation through time
24:32 - Gradient issues
28:57 - Long short term memory (LSTM)
37:36 - RNN applications
41:30 - Attention
44:05 - Summary
Subscribe to stay up to date with new deep learning lectures at MIT, or follow us @MITDeepLearning on Twitter and Instagram to stay fully-connected!!
