Natural Language Processing with Deep Learning
CS224N
Investigate the fundamental concepts and ideas in natural language processing (NLP), and gain a thorough introduction to cutting-edge neural networks for NLP. You will develop an in-depth understanding of both the algorithms available for processing linguistic information and the underlying computational properties of natural languages. The focus is on deep learning approaches: implementing, training, debugging, and extending neural network models for a variety of language understanding tasks. You will progress from word-level and syntactic processing to coreference, question answering and machine translation. For your final project, you will apply a complex neural network model to a large-scale NLP problem.
Topics Include
- Computational properties of natural languages
- Coreference, question answering, and machine translation
- Processing linguistic information
- Syntactic and semantic processing
- Modern quantitative techniques in NLP
- Neural network models for language understanding tasks
What You Need to Succeed
- A conferred bachelor’s degree with an undergraduate GPA of 3.0 or better.
- Calculus and linear algebra, and one of the following— an introduction to natural language processing (CS124), an introduction to artificial intelligence (CS221), or machine learning (CS229).
What You Need To Get Started
Before enrolling in your first graduate course, you must complete an online application.
Don’t wait! While you can only enroll in courses during open enrollment periods, you can complete your online application at any time.
Once you have enrolled in a course, your application will be sent to the department for approval. You will receive an email notifying you of the department's decision after the enrollment period closes. You can also check your application status in your mystanfordconnection account at any time.
Learn more about the graduate application process.
