Announcements (for Winter 2017)
Welcome to CS224N!
Dear CS224N Students,
Lectures will be held in Skilling Auditorium. Attendance is encouraged as interactive tutorials and discussions will occur during lecture times.
The class website can be found at http://cs224n.stanford.edu (a.k.a., http://web.stanford.edu/class/cs224n/), where we will post all the course material this quarter including course announcements, so please be sure to frequently check for updates. A tentative syllabus is already up, so be sure to check it out if interested.
Further, we will be using OpenEdX for additional videos and weekly quizzes, which can be found here.
Discussion Forum and Contact Staff:
We will also be using Piazza as the primary tool for discussions this quarter. You can find the class webpage on Piazza at https://piazza.com/stanford/fall2015/cs224n. Please post all questions to Piazza including private messages to instructors (Piazza allows for posts to be made visible only to instructors) as those posts will be responded to first. E-mails sent to the staff should be sent to the staff mailing list (email@example.com) instead of individual staff e-mail address.
Please don't hesitate to contact us if you have any questions. Looking forward to a great quarter!
This year's final project reports are online now!
This course introduces the fundamental concepts and ideas in natural language processing (NLP), otherwise known as computational linguistics. Ever wondered how Google Translate works, or how companies do automated resume processing? Want to build a computer that understands language? This course is for you. It develops an in-depth understanding of both algorithms for processing linguistic information and the underlying computational properties of natural languages. We consider word-level, syntactic, and semantic processing from both a linguistic and an algorithmic perspective, aiming to get up to speed with current research in the area. The course focuses on modern quantitative techniques in NLP -- using large corpora, statistical models for acquisition, disambiguation, and parsing -- and the construction of representative systems.
Understanding language is a very complex thing -- but something that humans are amazingly good at:
Piazza: CS224N forum
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