Schedule

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• Chapter 1: Introduction

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• Chapter 2: Words and Tokens (Section 2.7)

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• Chapter 2: Words and Tokens

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• Chapter 2: Words and Tokens

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• Chapter 3: N-gram Language Models

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• Chapter 17: Sequence Labeling for Parts of Speech and Named Entities

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• Appendix I: Word Senses and WordNet

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• Chapter 5: Embeddings

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• Chapter 4: Logistic Regression and Text Classification
• Appendix B: Naive Bayes Classification

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• Chapter 4: Logistic Regression and Text Classification

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• Chapter 6: Neural Networks

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• Chapter 6: Neural Networks

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• Chapter 12: Machine Translation

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• Chapter 8: Transformers

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• Chapter 7: Large Language Models

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• Chapter 18: Context-Free Grammars and Constituency Parsing
• Chapter 19: Dependency Parsing

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• Appendix: Word Senses and WordNet

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• Chapter 25: Conversation and its Structure

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• Chapter 21: Semantic Role Labeling

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• Appendix K: Frame-based Dialogue Systems

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• Chapter 24: Discourse Coherence
• Chapter 23: Coreference Resolution and Entity Linking

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• Chapter 11: Information Retrieval and Retrieval-Augmented Generation

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• THE CURIOUS CASE OF NEURAL TEXT DeGENERATION
• Hierarchical Neural Story Generation

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• Get To The Point: Summarization with Pointer-Generator Networks

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• Learning Transferable Visual Models From Natural Language Supervision
• ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks

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• TBD

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