A practical introduction perfect for final-year undergraduate and graduate students without a solid background in linear algebra and calculus.

This book provides a thorough introduction to the formal foundations and practical applications of Bayesian networks. It provides an extensive discussion of tec

The first unified treatment of time series modelling techniques spanning machine learning, statistics, engineering and computer science.

Bayesian methods for machine learning have been widely investigated, yielding principled methods for incorporating prior information into inference algorithms.

This book provides a multi-level introduction to Bayesian reasoning (as opposed to “conventional statistics”) and its applications to data analysis. The bas