This book provides a hands-on introduction to Machine Learning (ML) from a multidisciplinary perspective that does not require a background in data science or computer science. It explains ML using simple language and a straightforward approach guided by real-world examples in areas such as health informatics, information technology, and business analytics. The book will help readers understand the various key algorithms, major software tools, and their applications. Moreover, through examples from the healthcare and ...
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This book provides a hands-on introduction to Machine Learning (ML) from a multidisciplinary perspective that does not require a background in data science or computer science. It explains ML using simple language and a straightforward approach guided by real-world examples in areas such as health informatics, information technology, and business analytics. The book will help readers understand the various key algorithms, major software tools, and their applications. Moreover, through examples from the healthcare and business analytics fields, it demonstrates how and when ML can help them make better decisions in their disciplines. The book is chiefly intended for undergraduate and graduate students who are taking an introductory course in machine learning. It will also benefit data analysts and anyone interested in learning ML approaches.
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Add this copy of Machine Learning for Practical Decision Making to cart. $98.87, new condition, Sold by discount_scientific_books rated 3.0 out of 5 stars, ships from Sterling Heights, MI, UNITED STATES, published 2022 by Springer International Publishing AG.
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New. Print on demand Contains: Illustrations, black & white. International Series in Operations Research & Management Science . XVII, 465 p. 1 illus. Intended for college/higher education audience.
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