BayesianReasoningandMachineLearning

Bayesian Reasoning and Machine Learning Extracting value from vast amounts of data presents a major challenge to all those working in computer science and related fields. Machine learning technology is already used to help with this task in a wide range of industrial applications, including search engines, DNA sequencing, stock market analysis and robot locomotion. As its usage becomes more widespread, the skills taught in this book will be invaluable to students. Designed for final-year undergraduate and graduate students, this gentle introduction is ideally suited to readers without a solid background in linear algebra and calculus. It covers basic probabilistic reasoning to advanced techniques in machine learning, and crucially enables students to construct their own models for real-world problems by teaching them what lies behind the methods. A central conceptual theme is the use of Bayesian modelling to describe and build inference algorithms. Numerous examples and exercises are included in the text. Comprehensive resources for students and instructors are available online. Bayesian Reasoning and Machine Learning David Barber Unive......