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Classroom Contents
Recurrent Neural Networks, Transformers, and Attention - MIT 6.S191 Lecture 2
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- 1 - Introduction
- 2 - Sequence modeling
- 3 - Neurons with recurrence
- 4 - Recurrent neural networks
- 5 - RNN intuition
- 6 - Unfolding RNNs
- 7 - RNNs from scratch
- 8 - Design criteria for sequential modeling
- 9 - Word prediction example
- 10 - Backpropagation through time
- 11 - Gradient issues
- 12 - Long short term memory LSTM
- 13 - RNN applications
- 14 - Attention fundamentals
- 15 - Intuition of attention
- 16 - Attention and search relationship
- 17 - Learning attention with neural networks
- 18 - Scaling attention and applications
- 19 - Summary
