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YouTube

Recurrent Neural Networks, Transformers, and Attention

Alexander Amini via YouTube

Overview

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This lecture introduces sequence modeling with recurrent neural networks, covering their intuition, implementation, backpropagation through time, gradient issues, LSTMs, and attention mechanisms.

Syllabus

​ - Introduction
​ - Sequence modeling
​ - Neurons with recurrence
- Recurrent neural networks
- RNN intuition
​ - Unfolding RNNs
- RNNs from scratch
- Design criteria for sequential modeling
- Word prediction example
​ - Backpropagation through time
- Gradient issues
​ - Long short term memory LSTM
​ - RNN applications
- Attention fundamentals
- Intuition of attention
- Attention and search relationship
- Learning attention with neural networks
- Scaling attention and applications
- Summary

Taught by

https://www.youtube.com/@AAmini/videos

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