Neural Nets for NLP - Class Introduction & Why Neural Nets?

Neural Nets for NLP - Class Introduction & Why Neural Nets?

Graham Neubig via YouTube Direct link

Intro

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1 of 23

Intro

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Classroom Contents

Neural Nets for NLP - Class Introduction & Why Neural Nets?

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  1. 1 Intro
  2. 2 Are These Sentences OK?
  3. 3 Engineering Solutions
  4. 4 Phenomena to Handle
  5. 5 An Example Prediction Problem: Sentence Classification
  6. 6 A First Try: Bag of Words (BOW)
  7. 7 Build It, Break It
  8. 8 Combination Features
  9. 9 Basic Idea of Neural Networks (for NLP Prediction Tasks)
  10. 10 An edge represents a function argument (and also an data dependency). They are just pointers to nodes
  11. 11 Algorithms (1)
  12. 12 Forward Propagation
  13. 13 Algorithms (2)
  14. 14 Basic Process in Dynamic Neural Network Frameworks
  15. 15 Computation Graph and Expressions
  16. 16 Model and Parameters
  17. 17 Parameter Initialization
  18. 18 Trainers and Backdrop
  19. 19 Training with DyNet
  20. 20 Continuous Bag of Words (CBOW) movie
  21. 21 What do Our Vectors Represent?
  22. 22 Things to Remember
  23. 23 Class Format

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