Probabilistic Graph Models

If you are a researcher or a machine learning enthusiast, or are working in the data science field and have a basic idea of Bayesian learning or probabilistic graphical models, this book will help you to understand the details of graphical models and use them in your data science problems.

Create effective data science projects and avoid common pitfalls with the help of examples and hints dictated by experience. The book starts by introducing you to setting up your essential data science toolbox.

by Rina Dechter (Author)
Graphical models (e.g., Bayesian and constraint networks, influence diagrams, and Markov decision processes) have become a central paradigm for knowledge representation and reasoning in both artificial intelligence and computer science in general