This book is a collection of interdisciplinary paradigms related to two important research fields, biomedical signal processing, especially related to EEG signal processing and machine learning/soft c
This book explains the complete loop to effectively use self-tracking data for machine learning. While it focuses on self-tracking data, the techniques explained are also applicable to sensory data in
"This book presents some new ideas about estimation and evaluation of the quality of software and using a standard conversion method so that lines of code from any language may be compared and be used
Molecular biologists are performing increasingly large and complicated experiments, but often have little background in data analysis. The book is devoted to teaching the statistical and computational
Peer learning allows a positive use of differences between pupils, turning them into learning opportunities. Yet education professionals often remain unfamiliar with the principles necessary to guaran
Peer learning allows a positive use of differences between pupils, turning them into learning opportunities. Yet education professionals often remain unfamiliar with the principles necessary to guaran
Learning Chinese can be frustrating and difficult, partly because it’s very different from European languages. Following a teacher, textbook or language course is not enough. They show you the charact
Computational Statistics and Machine Learning: A Sparse Approach focuses on using sparse algorithms in statistics and machine learning. The first part addresses the L_0 norm minimization using greedy
This book describes the latest developments in nonlinear methods and their application in fault diagnosis. It details advances in machine learning theory and contains numerous case studies with real-w
As the power of computing has grown over the past few decades, the field of machinelearning has advanced rapidly in both theory and practice. Machine learning methods are usuallybased on the assumptio
This book provides a thorough introduction to the most important topics in data mining and machine learning. All the topics covered have undergone rapid development and this treatment offers a modern
A variety of problems in machine learning and digital communication deal with complexbut structured natural or artificial systems. In this book, Brendan Frey uses graphical models as anoverarching fra
