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

Machine learning methods extract value from vast data sets quickly and with modest resources. They are established tools in a wide range of industrial applicati

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.

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