Many forms of perception and action can be mathematically modeled using probabilistic (Bayesian) inference, a method used to derive conclusions from uncertain data. According to these models, when faced with noisy and ambiguous data, the human brain behaves like a talented data scientist or crime scene investigator. This book, rich in examples and illustrations, is an introduction to the methodology for building and using probabilistic decision and action models. The publication is addressed to a wide range of readers interested in neuroscience, cognitive sciences, machine learning, psychology, linguistics and mathematics.