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