hankcs/CS224n

CS224n: Natural Language Processing with Deep Learning Assignments Winter, 2017

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This project provides assignments and practical examples for understanding core concepts in Natural Language Processing (NLP) using deep learning. It takes raw text or structured language data and demonstrates how to process it to extract meaning, categorize sentiment, or parse grammatical structure. This is designed for individuals learning or teaching advanced NLP techniques, such as university students, researchers, or data scientists transitioning into language-focused AI.

683 stars. No commits in the last 6 months.

Use this if you are studying or teaching deep learning for Natural Language Processing and need practical assignments to apply concepts like word embeddings, sentiment analysis, dependency parsing, or named entity recognition.

Not ideal if you are looking for a plug-and-play tool or library for immediate use in a production NLP application, as this focuses on educational assignments.

Natural Language Processing Deep Learning Sentiment Analysis Named Entity Recognition Dependency Parsing
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 25 / 25

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Stars

683

Forks

270

Language

Python

License

GPL-3.0

Last pushed

Oct 15, 2018

Commits (30d)

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