Pattern Recognition and Machine Learning Christopher M. Bishop is an English-language textbook that focuses on pattern recognition and machine learning. This reference work provides a professional and accessible introduction to these fields, suitable for advanced students and researchers.
The book covers the origins of recognition and machine learning in engineering and computer science, respectively. Bayesian methods and graphical models are explained clearly, as well as modern techniques such as variational Bayes and kernel methods. This creates a complete overview of the key concepts and algorithms in pattern recognition and machine learning.
This edition aligns with topics such as Artificial Intelligence, Computer Vision, and Pattern Recognition, and is of interest to anyone who wants to explore data analysis and probabilistic models in both practical and theoretical ways.
Series: Information Science and Statistics