Natural Language Processing

CSE392 - Spring 2019

Slides are intended as a visual aid for the lecture given in class. They are not a comprehensive set of class notes or a replacement for the readings.

• Topic 1: Introduction and Preliminaries: Regular Expressions and Probability
• Topic 2: Part of Speech Tagging and Logistic Regression [ logistic regression code , LogReg showing benefit of regularization ]
• Topic 3: Language Modeling [ Word, Bigram, Trigram Counting and Modeling ]
• Topic 4: Introduction to RNNs and TensorFlow
• Topic 5: Semantics Avalanche: WSD, Dep Parsing, SRL/VerbPred
• Topic 6: Vector Semantics (Word Embeddings)
• Topic 7: RNN-based Language Modeling
• Topic 8: Human Centered NLP, Diff. Lang. Analysis, Ethics
• Topic 9: Transformers and Machine Translation