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Over the years, research in machine learning has been tracked with variable degrees of intensity, putting diverse approaches and employing emphasis on different, aspects and goals. This book is packed with diverse approaches aims to provide an up-to-date and systematical introduction to the principles and algorithms of machine learning. The book will be of particular interest to industrial engineers and scientists as well as academics who wish to pursue machine learning. The book is envisioned to both graduate and postgraduate students in fields such as computer science, cybernetics, system sciences, engineering, statistics, and social sciences, and as an invaluable reference tool for software professionals and practitioners.
