NLP for extracting meaning from text and social networks on the web, and interacting with people via language. Introducing methods (from regex to large language models, via logistic regression, gradient descent, transformers and other neural networks, social networks, collaborative filtering), applications (chatbots, information retrieval, social computing, recommender systems), and ethical and social issues. Prerequisites: CS 106B, Python (at the level of CS 106A), CS 109 (or equivalent background in probability), and programming maturity and knowledge of UNIX equivalent to CS 107 (or taking CS 107 or CS 1U concurrently).
3-4 units · Letter or Credit/No Credit · GER: WAY-AQR
NLP for extracting meaning from text and social networks on the web, and interacting with people via language. Introducing methods (from regex to large language models, via logistic regression, gradient descent, transformers and other neural networks, social networks, collaborative filtering), applications (chatbots, information retrieval, social computing, recommender systems), and ethical and social issues. Prerequisites: CS106B, Python (at the level of CS106A), CS109 (or equivalent background in probability), and programming maturity and knowledge of UNIX equivalent to CS107 (or taking CS107 or CS1U concurrently).
Offered in Winter 2027 at Stanford University.