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CS224n: Natural Language Processing with Deep Learning

What is cs224n and cs224d?
This course was formed in 2017 as a merger of the earlier CS224n (Natural Language Processing) and CS224d (Natural Language Processing with Deep Learning) courses. Below you can find archived websites and student project reports. All class assignments will be in Python (using NumPy and PyTorch ).
Are deep learning models used in natural language processing (NLP)?
Recently, a variety of model designs and methods have blossomed in the context of natural language processing (NLP). In this paper, we review significant deep learning related models and methods that have been employed for numerous NLP tasks and provide a walk-through of their evolution.
What is deep learning linguistics?
Methods for processing human language information and the underlying computational properties of natural languages. Focus on deep learning approaches: understanding, implementing, training, debugging, visualizing, and extending neural network models for a variety of language understanding tasks.
How do I enroll in cs224n?
Stanford students enroll normally in CS224N and others can also enroll in CS224N via Stanford online in the (northern hemisphere) Autumn to do the course in the Winter (high cost, limited enrollment, gives Stanford credit). The lecture slides and assignments are updated online each year as the course progresses.

What is cs224n and cs224d?