Bayesian Models for Social Interactions - 2013
Offered By: Center for Language & Speech Processing(CLSP), JHU via YouTube
Course Description
Overview
Explore a comprehensive lecture on Bayesian models for social interactions presented by Katherine Heller in 2013. Delve into the application of Bayesian statistical methods to analyze and understand complex social dynamics. Learn how these models can be used to interpret human behavior, predict social patterns, and make inferences about social networks. Gain insights into the mathematical foundations and practical implementations of Bayesian approaches in social science research. Discover the potential of these models to uncover hidden structures in social data and improve decision-making processes in various fields, including psychology, sociology, and marketing. Enhance your understanding of probabilistic reasoning and its relevance to social interaction studies through this in-depth presentation from the Center for Language & Speech Processing at Johns Hopkins University.
Syllabus
Bayesian Models for Social Interactions - Katherine Heller - 2013
Taught by
Center for Language & Speech Processing(CLSP), JHU
Related Courses
Artificial IntelligenceMassachusetts Institute of Technology via MIT OpenCourseWare Bayesian Networks 2 - Forward-Backward - Stanford CS221: AI
Stanford University via YouTube Bayesian Networks 1 - Inference - Stanford CS221: AI
Stanford University via YouTube AI & ML in Cyber Security - Why Algorithms Are Dangerous
Black Hat via YouTube Probabilistic Scripts for Automating Common-Sense Tasks
Strange Loop Conference via YouTube