Topic: Machine Learning

This book explores new developments, ideas, and concepts in intelligent edge-embedded technologies for the digitising industry. The work is based on recent research results and activities in edge industrial computing,...

This book is based on my five day course which I had the pleasure of teaching in the following Spanish cities: A Coruña, Algeciras, Alicante, Bilbao, Cáceres, Granada, Huesca, Jaén,...

This open access book provides a basic introduction to feature modelling and analysis as well as to the integration of AI methods with feature modelling. It is intended as an...

This open access book constitutes the revised selected papers of the First International Symposium on AI, Data and Digitalization, SAIDD 2023, held in Sogndal, Norway, during May 9–10, 2023. The...

This open access comprehensive methodological book offers a much-needed answer to the lack of resources and methodological guidance in learning analytics, which has been a problem ever since the field...

This open access book provides a detailed review of the latest methods and applications of artificial intelligence (AI) and machine learning (ML) in medicine. With chapters focusing on enabling the...

This book contains two parts, the first is designed to be used in an introductory programming course for students looking to learn Python, without having any prior experience with programming....

We will cover Large Language Models, Deep Learning, general Machine Leaning and good old fashioned Symbolic AI, broad coverage of data sources as well as wide range of tips and...

Using real-world data case studies, this innovative and accessible textbook introduces an actionable framework for conducting trustworthy data science. Most textbooks present data science as a linear analytic process involving...

We survey the nascent literature on machine learning in the study of financial markets. We highlight the best examples of what this line of research has to offer and recommend...

This monograph is motivated by a number of recent developments that appear to define a possible new role for researchers with an engineering profile. First, there are now several software...

A comprehensive and self-contained introduction to Gaussian processes, which provide a principled, practical, probabilistic approach to learning in kernel machines. Gaussian processes (GPs) provide a principled, practical, probabilistic approach to...