Last week, I finally received my copy of C. M. Bishop’s new textbook titled Pattern Recognition and Machine Learning. After reading through it for the last few days, I have to admit that this is one of the most comprehensive and up to date textbooks on the subject available today. Bishop who is a research scientist at Microsoft Research Cambridge and holds a Chair in Computer Science at the University of Edinburgh has written a complete treatment of machine learning in 738 pages suitable for young scientists at the advanced undergraduate and early graduate level. Indeed reading this book requires a certain background in math and computer science. However, Bishop starts by explaining the most basic concepts first so anyone with a bit of extra effort could potentially read and understand this excellent textbook; some familiarity with multivariate calculus and linear algebra certainly would help.
As I mentioned earlier, this is a textbook. Each chapter includes a number of exercises including some for which the solutions are available on the book’s website; these exercises are clearly marked in the book. Bishop has done an excellent job with this book. He explains many advanced concepts very clearly. The illustrations and examples found in the book further aid in the assimilation of these concepts. The book starts discussing basic concepts such as probability, decision and information theory and then moves on to present regression, classification, neural networks and kernel methods. In the second half of the book, Bishop presents graphical models, inference (exact and approximate,) sampling methods and finally how to model sequential data.
Bishop is currently working on a companion volume which will include example source code implementing many of the algorithms presented in the book along with the appropriate data sets in order to help students better understand all the key concepts. The book which Bishop is co-authoring with Ian T. Nabney should be available in 2008.