Bayesian Reasoning and Gaussian Processes for Machine Learning Applications

This book provides an introduction to Bayesian reasoning and Gaussian processes for machine learning applications, covering topics such as belief networks, Bayesian reinforcement learning, Gaussian process introduction, classification, regression, covariance, and performance analysis. It is aimed at graduates, researchers, and professionals in data science and machine learning.

Format: Hardback
Length: 133 pages
Publication date: 14 April 2022
Publisher: Taylor & Francis Ltd

Bayesian reasoning and Gaussian processes have revolutionized machine learning applications, offering a powerful approach to understanding and analyzing data. In this comprehensive book, we delve into the world of Bayesian methods, which are widely applied in diverse fields such as game development, decision-making, and drug discovery. By leveraging a statistical background, we gain insights into continuous distributions and how learning can be approached from a probabilistic perspective.

The book progresses seamlessly into various machine learning topics, including belief network and Bayesian reinforcement learning, which are essential for developing robust and efficient learning algorithms. We then explore the fundamentals of Gaussian processes, covering classification, regression, covariance, and performance analysis.

One of the key strengths of Bayesian methods is their ability to handle missing data and extract valuable information from small datasets. This makes them particularly valuable in scenarios where data is scarce or incomplete. The book includes numerous case studies and real-world examples to illustrate the practical applications of Bayesian reasoning and Gaussian processes in data science and machine learning.

Whether you are a graduate student, researcher, or professional in the field of data science and machine learning, this book offers valuable insights and advancements in the field. It provides a comprehensive coverage of Bayesian methods, Gaussian processes, and their applications, making it an essential resource for anyone seeking to stay at the forefront of this rapidly evolving field.

Dimension: 254 x 178 (mm)
ISBN-13: 9780367758479