MIT 6.S191: Introduction to Deep Learning - 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 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!!