Completed
Intro
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Classroom Contents
Neural Nets for NLP: Recurrent Neural Networks
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- 1 Intro
- 2 NLP and Sequential Data
- 3 Long-distance Dependencies in Language
- 4 Can be Complicated!
- 5 Unrolling in Time
- 6 Training RNNS
- 7 Parameter Tying
- 8 What Can RNNs Do?
- 9 Representing Sentences
- 10 Representing Contexts
- 11 e.g. Language Modeling
- 12 RNNLM Example: Loss Calculation and State Update
- 13 LSTM Structure
- 14 Other Alternatives
- 15 Handling Mini-batching
- 16 Mini-batching Method
- 17 Bucketing/Sorting
- 18 Handling Long Sequences
- 19 RNN Strengths/Weaknesses
- 20 Pre-training/Transfer
