An accessible guide to machine learning principles for programmers. Features hands-on example projects, real-world case studies, and easy-to-understand explanations.Practical Machine Learning is a cle
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
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
