Neural Nets for NLP 2021 - Recurrent Neural Networks

Neural Nets for NLP 2021 - Recurrent Neural Networks

Graham Neubig via YouTube Direct link

Intro

1 of 21

1 of 21

Intro

Class Central Classrooms beta

YouTube videos curated by Class Central.

Classroom Contents

Neural Nets for NLP 2021 - Recurrent Neural Networks

Automatically move to the next video in the Classroom when playback concludes

  1. 1 Intro
  2. 2 NLP and Sequential Data
  3. 3 Long-distance Dependencies in Language
  4. 4 Can be Complicated!
  5. 5 Recurrent Neural Networks (Elman 1990)
  6. 6 Training RNNS
  7. 7 Parameter Tying
  8. 8 What Can RNNs Do?
  9. 9 Representing Sentences
  10. 10 e.g. Language Modeling
  11. 11 Vanishing Gradient . Gradients decrease as they get pushed back
  12. 12 A Solution: Long Short-term Memory (Hochreiter and Schmidhuber 1997)
  13. 13 LSTM Structure
  14. 14 What can LSTMs Learn? (1)
  15. 15 Handling Mini-batching
  16. 16 Mini-batching Method
  17. 17 Bucketing/Sorting
  18. 18 Optimized Implementations of LSTMs (Appleyard 2015)
  19. 19 Gated Recurrent Units (Cho et al. 2014)
  20. 20 Soft Hierarchical Stucture
  21. 21 Handling Long Sequences

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.