Machine Learning for Practical Decision Making A Multidisciplinary Perspective with Applications from Healthcare, Engineering and Business Analytics
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 i...
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Otros Autores: | , , |
Formato: | Libro electrónico |
Idioma: | Inglés |
Publicado: |
Cham :
Springer International Publishing
2022.
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Edición: | 1st ed. 2022. |
Colección: | Springer eBooks.
International Series in Operations Research & Management Science ; 334. |
Acceso en línea: | Conectar con la versión electrónica |
Ver en Universidad de Navarra: | https://innopac.unav.es/record=b47355852*spi |
Sumario: | 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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Descripción Física: | 1 recurso electrónico, XVII, 465 páginas, 1 ilustraciones |
Formato: | Forma de acceso: World Wide Web. |
ISBN: | 9783031169908 |