Probabilistic_Graphical_Models:_Principles_And_Techniques
Probabilistic_Graphical_Models:_Principles_And_Techniques
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Probabilistic Graphical Models: Principles And Techniques

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Product Information

Brand

Pagify


Ideal For

Reading


Material

Paper


Country Of Origin

India


Pack Of

1


Author

Daphne Koller & Nir Friedman


Genre

Science & Mathematics


Isbn

9780000000000


Page Count

1270


Product Type

Book

Product Description


  • Premium Quality: Probabilistic Graphical Models discusses a variety of models, spanning Bayesian networks, undirected Markov networks, discrete and continuous models, and extensions to deal with dynamical systems and relational data.

  • Product Design: For each class of models, the text describes the three fundamental cornerstones: representation, inference, and learning, presenting both basic concepts and advanced techniques.

  • User Experience: The book considers the use of the proposed framework for causal reasoning and decision making under uncertainty, offering a rigorous yet accessible treatment of the subject.

  • Versatile Occasion: The main text in each chapter provides the detailed technical development of the key ideas, while most chapters also include boxes with additional material such as skill boxes and case study boxes discussing empirical cases related to the approach described.

  • Quality Assurance: At 1,270 pages and published under ISBN 9780262013192, this Pagify edition is printed on quality paper and represents an authoritative reference for students and researchers in science and mathematics.

  • Ideal For: This comprehensive volume is ideal for graduate students, researchers, and practitioners seeking a deep and structured understanding of probabilistic graphical models and their real-world applications.