cs224n and stanford-cs224n
These are complements: the first is a complete course implementation covering both lecture materials and assignments from Winter 2020, while the second provides reference solutions specifically for the problem sets from the earlier 2017 iteration, allowing students to cross-reference their work across different years of the same course.
About cs224n
leehanchung/cs224n
Stanford CS224n: Natural Language Processing with Deep Learning, Winter 2020
This project is a personal study guide for Stanford's CS224n course on Natural Language Processing with Deep Learning. It walks through assignments that involve building word embeddings, implementing Word2Vec, and developing neural machine translation systems using recurrent neural networks. Anyone learning or teaching advanced NLP concepts, especially those without access to an autograder, would find this helpful.
About stanford-cs224n
zyxue/stanford-cs224n
Exercise answers to the problem sets from CS224n: Natural Language Processing with Deep Learning Winter quarter (January - March, 2017)
This resource provides comprehensive answers and detailed derivations for the problem sets from Stanford's CS224n: Natural Language Processing with Deep Learning course. If you're a student enrolled in a similar NLP course or self-studying the material, you can use these notebooks to check your work and understand complex concepts like backpropagation. It's designed for computer science students, researchers, or anyone learning deep learning applications in natural language processing.
Related comparisons
Scores updated daily from GitHub, PyPI, and npm data. How scores work