Machine Learning for Practical Decision Making: A Multidisciplinary Perspective with Applications from Healthcare, Engineering and Business Analytics

This book provides an introduction to Machine Learning (ML) from a multidisciplinary perspective, using simple language and real-world examples to demonstrate its applications in health informatics, information technology, and business analytics. It is intended for undergraduate and graduate students, data analysts, and anyone interested in learning ML approaches.

Format: Hardback
Length: 465 pages
Publication date: 30 November 2022
Publisher: Springer International Publishing AG

This comprehensive guide offers a hands-on introduction to Machine Learning (ML) from a multidisciplinary perspective, making it accessible to individuals without prior expertise in data science or computer science. Through the use of simple language and a straightforward approach, accompanied by real-world examples across various domains such as health informatics, information technology, and business analytics, the book aims to elucidate the concept of ML in a clear and concise manner. By providing a comprehensive overview of key algorithms, prominent software tools, and their practical applications, the book empowers readers to grasp the intricacies of ML and its potential to enhance decision-making across diverse fields.

Specifically designed for undergraduate and graduate students enrolled in introductory courses in machine learning, this resource also serves as a valuable resource for data analysts and anyone seeking to explore ML approaches. Each chapter is thoughtfully organized, presenting the fundamental concepts of ML in a step-by-step manner, while also incorporating practical examples and case studies to reinforce understanding and application.

The book's multidisciplinary approach ensures that readers gain a holistic understanding of ML, encompassing its theoretical foundations, computational techniques, and real-world applications. By exploring the use of ML in healthcare informatics, information technology, and business analytics, readers are equipped with the knowledge and tools necessary to apply ML in their respective fields and contribute to the development of innovative solutions.

Whether you are a student, professional, or simply interested in expanding your knowledge of ML, this book is an invaluable resource. Its comprehensive coverage, practical examples, and user-friendly style make it an essential guide for anyone seeking to delve into the world of machine learning and unlock its full potential.

Weight: 887g
Dimension: 235 x 155 (mm)
ISBN-13: 9783031169892
Edition number: 1st ed. 2022