MIT Introduction to Deep Learning : Lecture 2 Recurrent Neural Networks Lecturer: Ava Soleimany January 2021 For all lectures, slides, and lab materials: 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 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!!
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