Stanford NLP class in 2019, given by Professor Christopher Manning, is aimed at exploring the fundamental concepts of NLP and its role in current and emerging technologies.
What you will learn
- Computational properties of natural languages
- Neural network models for language understanding tasks
- Word vectors, syntactic, and semantic processing
- Coreference, question answering, and machine translation
Homework Projects
- Hw1 - an IPython Notebook
- Hw2 - Basic Numpy
- Hw3 - PyTorch Intro
- Hw4 and Hw5 - Use PyTorch on a GPU (Microsoft Azure)
Examples of Task
Easy
- Spell Checking
- Keyword Search
- Finding Synonyms
Medium
- Parsing information from websites, documents, etc.
Hard
- Machine Translation (e.g. Translate Chinese text to English)
- Semantic Analysis (What is the meaning of query statement?)
- Coreference (e.g. What does “he” or “it” refer to given a docu-ment?)
- Question Answering (e.g. Answering Jeopardy questions).
Acknowledgement
The original lecture video can be found at CS224N.