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CS224N: NLP with Deep Learning
How language models actually work, from the source.
Stanford's graduate course on natural language processing with deep learning, with lecture materials published openly. It goes from word vectors through to the architectures behind current language models.
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Course overview
This is a real university course rather than an introduction, and it expects comfort with linear algebra, calculus and Python.
What you will learn
- Understand word vectors and what they encode
- Follow the architecture of modern language models in detail
- Read and evaluate an NLP paper on its own terms
- Reason about training, evaluation and the limits of these systems
Who this course is for
Engineers with the maths
you want the source, not a summary
Graduate students
the reference course in the field
Course details
FormatUniversity lecture course with public materials
LevelAdvanced
PriceFree
Time45 hours
CertificateNo certificate
About Stanford
Stanford publishes lecture notes, slides and assignments for several of its graduate AI courses. These are real university courses rather than introductions, and they assume the mathematics that comes with that.
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