This is a short, practical guide that allows data scientists to understand the concepts of Graphical models and enables them to try them out using small Python code snippets, without being too mathematically complicated.
If you are a data scientist who knows about machine learning and want to enhance your knowledge of graphical models, such as Bayes nets, in order to use them to solve real-world problems using Python libraries, this book is for you.
This book is intended for those who have some Python and machine learning experience, or are exploring the machine learning field.
"synopsis" may belong to another edition of this title.
Kiran R Karkera is a telecom engineer with a keen interest in machine learning. He has been programming professionally in Python, Java, and Clojure for more than 10 years. In his free time, he can be found attempting machine learning competitions at Kaggle and playing the flute.
"About this title" may belong to another edition of this title.
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