Modeling and Reasoning with Bayesian Networks
Product Description
Modeling and Reasoning with Bayesian Networks
- Used Book in Good Condition
This book provides a thorough introduction to the formal foundations and practical applications of Bayesian networks. It provides an extensive discussion of techniques for building Bayesian networks that model real-world situations, including techniques for synthesizing models from design, learning models from data, and debugging models using sensitivity analysis. It also treats exact and approximate inference algorithms at both theoretical and practical levels. The author assumes very little background on the covered subjects, supplying in-depth discussions for theoretically inclined readers and enough practical details to provide an algorithmic cookbook for the system developer.
Technical Specifications
You might also like
The Book of Why: The New Science of Cause and Effect
Causality: Models, Reasoning and Inference
Machine Learning: A Probabilistic Perspective (Adaptive Computation and Machine Learning series)
Probabilistic Graphical Models: Principles and Techniques (Adaptive Computation and Machine Learning series)
Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning series)
Risk Assessment and Decision Analysis with Bayesian Networks
Bayesian Data Analysis (Chapman & Hall/CRC Texts in Statistical Science)
Introduction to Probability, Statistics, and Random Processes
Risk Assessment and Decision Analysis with Bayesian Networks
Statistical Rethinking: A Bayesian Course with Examples in R and Stan (Chapman & Hall/CRC Texts in Statistical Science)