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remember: backpropagation
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Classroom Contents
Sequence Modeling with Neural Networks
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- 1 Intro
- 2 What is a sequence?
- 3 a sequence modeling problem
- 4 idea: use a fixed window
- 5 problem: we can't model long-term dependencies
- 6 idea: use entire sequence, as a set of counts
- 7 idea: use a really big fixed window
- 8 problem: no parameter sharing
- 9 to model sequences, we need
- 10 example network
- 11 RNNS remember their previous state
- 12 "unfolding" the RNN across time
- 13 remember: backpropagation
- 14 let's try it out for W with the chain rule
- 15 backpropagation through time
- 16 problem: vanishing gradient
- 17 activation functions
- 18 initialization
- 19 gated cells
- 20 possible task: music generation
- 21 possible task: machine translation
- 22 problem: a single encoding is limiting
- 23 solution: attend over all encoder states
