https://web.stanford.edu/class/archive/cs/cs224n/cs224n.1214/
https://www.youtube.com/playlist?list=PLoROMvodv4rOSH4v6133s9LFPRHjEmbmJ
CS224N: Natural Language Processing with Deep Learning | Winter 2021
For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit:
stanfordonline
Natural language processing (NLP) or computational linguistics is one of the most important technologies of the information age.
Applications of NLP are everywhere because people communicate almost everything in language: web search, advertising, emails, customer service, language translation, virtual agents, medical reports, etc.
In recent years, deep learning (or neural network) approaches have obtained very high performance across many different NLP tasks, using single end-to-end neural models that do not require traditional, task-specific feature engineering.
In this course, students will gain a thorough introduction to cutting-edge research in Deep Learning for NLP.
Through lectures, assignments and a final project, students will learn the necessary skills to design, implement, and understand their own neural network models.
Introduction and Word Vectors
Neural Classifiers
Backprop and Neural Networks
Dependency Parsing
Language Models and RNNs
https://web.stanford.edu/class/archive/cs/cs224n/cs224n.1214/slides/cs224n-2021-lecture05-rnnlm.pdf
Simple and LSTM RNNs
Translation, Seq2Seq, Attention
https://web.stanford.edu/class/archive/cs/cs224n/cs224n.1214/slides/cs224n-2021-lecture07-nmt.pdf
Final Projects; Practical Tips
Self- Attention and Transformers
Transformers and Pretraining
Question Answering
https://web.stanford.edu/class/archive/cs/cs224n/cs224n.1214/slides/cs224n-2021-lecture11-qa-v2.pdf
Natural Language Generation
Coreference Resolution
https://web.stanford.edu/class/archive/cs/cs224n/cs224n.1214/slides/cs224n-2021-lecture13-coref.pdf
T5 and Large Language Models
https://web.stanford.edu/class/archive/cs/cs224n/cs224n.1214/slides/cs224n-2021-lecture14-t5.pdf
Add Knowledge to Language Models
https://web.stanford.edu/class/archive/cs/cs224n/cs224n.1214/slides/cs224n-2021-lecture15-lm.pdf
Social & Ethical Considerations
https://web.stanford.edu/class/archive/cs/cs224n/cs224n.1214/slides/cs224n-2021-lecture16-ethics.pdf
Model Analysis and Explanation
Future of NLP + Deep Learning
https://web.stanford.edu/class/archive/cs/cs224n/cs224n.1214/slides/cs224n-2021-lecture18-future.pdf
Winter 2020
Low Resource Machine Translation
Winter 2020
BERT and Other Pre-trained Language Models
https://web.stanford.edu/class/archive/cs/cs224n/cs224n.1204/slides/Jacob_Devlin_BERT.pdf