A new book that explores how machine learning can be applied to decision-making in practical settings is co-authored by three York faculty members along with a colleague from Ontario Health.
The textbook titled Machine Learning for Practical Decision Making: A Multidisciplinary Perspective with Applications from Healthcare, Engineering & Business Analytics offers real-life examples for novice readers with no previous technical background. It provides a hands-on approach to teach practical machine learning skills in health care, business and engineering applications.
Authors of the book are: Christo El Morr, associate professor of health informatics in York’s Faculty of Health; Manar Jammal, assistant professor of information technology in York’s Faculty of Liberal Arts & Professional Studies; Hossam Ali-Hassan, associate professor of business administration at York’s Glendon Campus; and Walid El-Hallak from Ontario Health.
“The book is intended to help students have a smooth introduction to machine learning using a hands-on approach,” said El Morr.
The book uses simple language, and a straightforward approach, to introduce machine learning, and will help readers understand key algorithms, major software tools, and their applications. Through real-world examples, the book demonstrates how and when to use machine learning in decision-making processes across various disciplines.
The book is 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 understanding machine learning approaches.
More information on the book is available online.
Originally published in YFile.