WAIC and WBIC with Python Stan
eBook - ePub

WAIC and WBIC with Python Stan

100 Exercises for Building Logic

  1. English
  2. ePUB (mobile friendly)
  3. Available on iOS & Android
eBook - ePub

WAIC and WBIC with Python Stan

100 Exercises for Building Logic

About this book

Master the art of machine learning and data science by diving into the essence of mathematical logic with this comprehensive textbook. This book focuses on the widely applicable information criterion (WAIC), also described as the Watanabe-Akaike information criterion, and the widely applicable Bayesian information criterion (WBIC), also described as the Watanabe Bayesian information criterion. The book expertly guides you through relevant mathematical problems while also providing hands-on experience with programming in Python and Stan. Whether you're a data scientist looking to refine your model selection process or a researcher who wants to explore the latest developments in Bayesian statistics, this accessible guide will give you a firm grasp of Watanabe Bayesian Theory.

The key features of this indispensable book include:

  1. A clear and self-contained writing style, ensuring ease of understanding for readers at various levels of expertise.
  2. 100 carefully selected exercises accompanied by solutions in the main text, enabling readers to effectively gauge their progress and comprehension.
  3. A comprehensive guide to Sumio Watanabe's groundbreaking Bayes theory, demystifying a subject once considered too challenging even for seasoned statisticians.
  4. Detailed source programs and Stan codes that will enhance readers' grasp of the mathematical concepts presented.
  5. A streamlined approach to algebraic geometry topics in Chapter 6, making Bayes theory more accessible and less daunting.

Embark on your machine learning and data science journey with this essential textbook and unlock the full potential of WAIC and WBIC today!

Information

Publisher
Springer
Year
2023
Print ISBN
9789819938407
eBook ISBN
9789819938414

Table of contents

  1. Cover
  2. Front Matter
  3. 1.Ā Overview of Watanabe’s Bayes
  4. 2.Ā Introduction to Watanabe Bayesian Theory
  5. 3.Ā MCMC and Stan
  6. 4.Ā Mathematical Preparation
  7. 5.Ā Regular Statistical Models
  8. 6.Ā Information Criteria
  9. 7.Ā Algebraic Geometry
  10. 8.Ā The Essence of WAIC
  11. 9.Ā WBIC and Its Application to Machine Learning
  12. Back Matter

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Yes, you can access WAIC and WBIC with Python Stan by Joe Suzuki in PDF and/or ePUB format, as well as other popular books in Computer Science & Artificial Intelligence (AI) & Semantics. We have over 1.5 million books available in our catalogue for you to explore.