This textbook, written by Simon Rogers and Mark Girolami, provides a clear introduction to machine learning for students and professionals. The new edition covers current topics in the field using theoretical and practical approaches.
The new edition includes three additional chapters on Markov Chain Monte Carlo, classification and regression with Gaussian Processes, and Dirichlet Process models. This ensures the book remains aligned with the latest developments in machine learning and statistical methods.
Features
- Author: Simon Rogers
- Publisher: Taylor & Francis Ltd
- Series: Chapman & Hall/CRC Machine Learning & Pattern Recognition
- Publication date: 30 June 2020
- Number of pages: 428
- ISBN: 9780367574642
- Theme: Econometrics and economic statistics
- BISAC: BUSINESS & ECONOMICS / Econometrics
About the authors
Simon Rogers is a lecturer at the School of Computing Science, University of Glasgow, with a focus on machine learning applied in computational biology and human-computer interaction.
Mark Girolami is a professor of Computer Science at the University of Warwick, with a background in statistics and a strong research career in computational statistics and machine learning.