Bayesian Reasoning and Gaussian Processes for Machine Learning Applications

By: Hemachandran K (Editor), Shubham Tayal (Editor), Preetha Mary George (Editor), Parveen Singla (Editor), Utku Kose (Editor)

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eText | 19 April 2022 | Edition Number 1

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This book introduces Bayesian reasoning and Gaussian processes into machine learning applications. Bayesian methods are applied in many areas, such as game development, decision making, and drug discovery. It is very effective for machine learning algorithms in handling missing data and extracting information from small datasets. Bayesian Reasoning and Gaussian Processes for Machine Learning Applications uses a statistical background to understand continuous distributions and how learning can be viewed from a probabilistic framework. The chapters progress into such machine learning topics as belief network and Bayesian reinforcement learning, which is followed by Gaussian process introduction, classification, regression, covariance, and performance analysis of Gaussian processes with other models.

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