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Mastering Probabilistic Graphical Models with Python Cover

Mastering Probabilistic Graphical Models with Python

Master probabilistic graphical models by learning through real-world problems and illustrative code examples in Python

Publisher:Packt Publishing Limited
Paid access
|Oct 2025
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Table of contents

Table of Contents

  1. Bayesian Network Fundamentals
  2. Markov Network Fundamentals
  3. Inference: Asking Questions to Models
  4. Approximate Inference Methods: Sampling
  5. Model Learning: Parameter Estimation in Bayesian Networks
  6. Model Learning: Parameter Estimation in Markov Networks
  7. Specialized Models
PDF ISBN: 978-1-78439-521-6
Publisher: Packt Publishing Limited
Copyright owner: © 2015 Packt Publishing Limited
Publication date: 2025
Language: English
Pages: 284
Related subjects:
General interest

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