Bayesian Reasoning and Gaussian Processes for Machine Learning Applications

The book Bayesian Reasoning and Gaussian Processes for Machine Learning Applications talks about Bayesian Reasoning and Gaussian Processes in 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 for handling missing data and for extracting information from small datasets. This book introduces a statistical background which is needed to understand continuous distributions and it gives an understanding on how learning can be viewed from a probabilistic framework. The chapters of the book progress into machine learning topics such as Belief Network, Bayesian Reinforcement Learning etc., which is followed by Gaussian Process Introduction, Classification, Regression, Covariance and Performance Analysis of GP with other models.Features . Contains recent advancement in machine learning. Highlights the applications of machine learning algorithms. Offers both quantitative and qualitative research. Includes lot of case studiesThis book is aimed primarily at graduates, researchers and professionals in the field of data science and machine learning.