Bayesian Networks for Causal Reasoning - Lecture 1

Explore the fundamentals of Bayesian Networks for causal reasoning in this lecture from the Machine Learning for Health and Disease program. Delve into the first part of Tavpritesh Sethi's presentation, which introduces key concepts and applications of Bayesian Networks in healthcare and biomedical research. Learn how these powerful probabilistic models can be used to infer causal relationships from data, aiding in decision-making processes and understanding complex health-related phenomena. Gain insights into the intersection of machine learning, statistics, and clinical practice as part of a comprehensive program designed to bridge the gap between computational modeling and real-world healthcare challenges.

Bayesian Networks for Causal Reasoning (Lecture 1) by Tavpritesh Sethi