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CMU Advanced NLP Fall 2024 (1): Introduction to NLP
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Classroom Contents
Advanced Natural Language Processing - Fall 2024
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- 1 CMU Advanced NLP Fall 2024 (1): Introduction to NLP
- 2 CMU Advanced NLP Fall 2024 (2): Representing Words
- 3 CMU Advanced NLP Fall 2024 (3): Language and Sequence Modeling
- 4 CMU Advanced NLP Fall 2024 (4): Attention and Transformers
- 5 CMU Advanced NLP Fall 2024 (5): Pre-training and Pre-trained Models
- 6 CMU Advanced NLP Fall 2024 (6): Instruction Tuning
- 7 CMU Advanced NLP Fall 2024 (7): Prompting and Complex Reasoning
- 8 CMU Advanced NLP Fall 2024 (8): Reinforcement Learning and Human Feedback
- 9 CMU Advanced NLP Fall 2024 (9): Experimental Design and Data Annotation
- 10 CMU Advanced NLP Fall 2024 (10): Retrieval and RAG
- 11 CMU Advanced NLP Fall 2024 (11): Distillation, Quantization, and Pruning
- 12 CMU Advanced NLP Fall 2024 (12): Domain Specific Modeling: Code and Math
- 13 CMU Advanced NLP Fall 2024 (13): Long Sequence Models
- 14 CMU Advanced NLP Fall 2024 (14): Ensembling and Mixture of Experts
- 15 CMU Advanced NLP Fall 2024 (15): Tool Use and LLM Agent Basics
- 16 CMU Advanced NLP Fall 2024 (16): Agents for Software Development and Web Browsing
- 17 CMU Advanced NLP Fall 2024 (17): Evaluation and Multimodal
- 18 CMU Advanced NLP Fall 2024 (18): Linguistics and Computational Linguistics
- 19 CMU Advanced NLP Fall 2024 (19): Learning From/For Knowledge Bases
- 20 CMU Advanced NLP Fall 2024 (20): Multilingual NLP
- 21 CMU Advanced NLP Fall 2024 (21): Safety, Ethics, and Biase in NLP Systems
- 22 CMU Advanced NLP Fall 2024 (22): From Decoding to Meta Generation Inference Time Algorithms for LMs
- 23 CMU Advanced NLP Fall 2024 (23): MagicPIG & Factor - Methods for Long Context LMs
