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Launch of “Fundamentals of Machine Learning”

Posted: 25 September, 2015

Dr. John Kelleher, lecturer in the DIT School of Computing, has co-authored a new book on the “Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Example, and Case Studies” with former colleague Dr. Brian McNamee of UCD and Aoife D’Arcy of the Analytics Store.

John Kelleher Homepage

The textbook, which was launched in Newman House this week, serves as an introduction to the key machine learning methods used in predictive data analytics. The book covers both theoretical concepts and practical applications for using machine learning for predictive data analytics and includes explanatory worked examples and case studies which aim to illustrate these examples in a broader business context.‌

The new publication is informed by Dr. Kelleher’s years of experience of teaching machine learning and working on various data analytics projects Speaking about the process of writing it, Kelleher and McNamee revealed that parts of the text had been devised whilst they were out surfing in Donegal, with the concept of learning to surf even serving as an illustrative model within the book itself. 

In addition to the three authors, other speakers at the launch were Professor Pádraig Cunningham, Head of UCD School of Computer Science and Professor Brian O’Neill, Director of Research, Enterprise & Innovation Services for the TU4Dublin alliance of DIT, ITB and ITT.

Speaking afterwards Dr. Kelleher said:

“We set out to write a machine learning book that was relevant and accessible, and I believe we have achieved that. The book covers the complete life-cycle of a predictive analytics project, from business problem through to model deployment and maintenance. At the same time, it provides comprehensive explanations of the most important machine learning algorithms. I am particularly proud of the fact that throughout the book we have provided detailed and complete worked examples. These examples are the most direct way of illustrating how machine learning theory can be used to solve concrete real-world problems.”

The book is published by MIT Press and for more info you can visit: