Building Probabilistic Graphical Models with Python

Building Probabilistic Graphical Models with Python | Packt Publishing

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Solve machine learning problems using probabilistic graphical models implemented in Python with real-world applications

With the increasing prominence in machine learning and data science applications, probabilistic graphical models are a new tool that machine learning users can use to discover and analyze structures in complex problems. The variety of tools and algorithms under the PGM framework extend to many domains such as natural language processing, speech processing, image processing, and disease diagnosis. You've probably heard of graphical models before, and you're keen to try out new landscapes in the machine learning area. This book gives you enough background information to get started on graphical models, while keeping the math to a minimum.

Details
Herausgeber Packt Publishing
Autor(en) Kiran R Karkera
ISBN 978-1-78328-900-4
veröffentlicht 2014
Seiten 172
Sprache English

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