Mastering Probabilistic Graphical Models Using Python: Master probabilistic graphical models by learning through real-world problems and illustrative code examples in Python

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 it in your data science problems. This book will also help you select the appropriate model as well as the appropriate algorithm for your problem.

Ankur Ankan

Ankur Ankan is a BTech graduate from IIT (BHU), Varanasi. He is currently working in the field of data science. He is an open source enthusiast and his major work includes starting pgmpy with four other members. In his free time, he likes to participate in Kaggle competitions.

Abinash Panda

Abinash Panda is an undergraduate from IIT (BHU), Varanasi, and is currently working as a data scientist. He has been a contributor to open source libraries such as the Shogun machine learning toolbox and pgmpy, which he started writing along with four other members. He spends most of his free time on improving pgmpy and helping new contributors.