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Pattern Recognition And Machine Learning introduces the reader to the latest developments in the field of pattern recognition and machine learning. It has broad coverage on topics related to statistics, computer science, machine learning, data mining, signal processing, computer vision and bioinformatics. Summary Of The Book Machine learning is a branch of artificial intelligence that deals with the study and construction of systems that learn from data. It has a number of useful applications, one among them being the automatic recognition of printed characters. Pattern recognition that is used in various fields such as psychiatry, computer science, psychology and traffic flow is the assigning of a label to a particular input value. Pattern recognition traces its origins to engineering, while machine learning grew out of computer science. The field of pattern recognition and machine learning has undergone a lot of changes in the past decade. For instance, Bayesian methods have become mainstream now as compared to being a specialist niche a few years ago. Similarly, graphical models too have become part of a general framework while describing and applying probabilistic models. Pattern Recognition And Machine Learning reflects such recent developments and also provides an in-depth introduction to the subjects of pattern recognition and machine learning. It is targeted at advanced undergraduates, first year Ph.D. students, researchers, practitioners or just about anyone who may not even have prior knowledge of the subject. Pattern Recognition And Machine Learning includes over 400 exercises that have been included with the intention of helping the reader reinforce the concepts discussed in each of the chapters and have been graded according to their difficulty level. About Christopher M. Bishop Christopher M. Bishop is a scientist, professor and writer. Other books written by him are Neural Networks For Pattern Recognition and Pulsed Neural Networks. Bishop was born on April 7, 1959. He is a holder of a B.A. degree in Physics from St Catherine's College, Oxford and a Ph.D. in Theoretical Physics from the University of Edinburgh. His interests include neural networks, natural language processing, machine learning and pattern recognition. Presently, he is a scientist at Microsoft Research Ltd, Cambridge. Bishop has been honoured as a Fellow of the Royal Academy of Engineering in 2004 and as a Fellow of the Royal Society of Edinburgh in 2007.