Winner, 2009 DeGroot Prize for best book in statistical science, which is given by the International Society for Bayesian Analysis. Gaussian process (doctors) to provide, principled practical, probabilistic approach to learning in kernel machines. Doctors have received increasing attention in the machine-learning community over the past decade, and this book provides a systematic and integrated treatment that takes a long theoretical and practical aspects of the physician in machine learning. Many other well-known connection techniques from machine learning and statistics are discussed, including support-vector machines, neural networks, splines, regularization networks, relevance vector machines and others. Theoretical issues including learning curves and the PAC-Bayesian framework are treated, and methods of several approaches to learning with large datasets are discussed.