Machine Learning meets Real World: A Paradigm Shift
Over the last few years there has been a surge in exploring how to leverage on data analytics/business analytics/data science to bring value to organization in three areas of 1. Increase Revenue 2. Improve Efficiency and 3. Non-compliance detection/ predictions. However, how does Machine Learning become Business Analytics? What are the other aspects that one’s needs to consider to achieve successful application. In this session we discuss the considerations of the shift and the value that can be ultimately derived.
Dr. David R. Hardoon is a Chief of Analytics at Azendian. Previously he was a director at Ernst & Young Advisory Pte. Ltd. where he led the advanced analytics practice and is responsible for the positioning of business analytics advisory and services to clients across different business sectors across ASEAN. Previous to his post at Ernst & Young, he had established expertise in developing and applying computational analytical models for business knowledge discovery and analysis through his involvement in a number of research projects in the domains of taxonomy, neuroscience, aerospace and finance. He received a B.Sc. in Computer Science and Artificial Intelligence with first class honors at Royal Holloway, University of London in 2002 and a PhD in Computer Science in the field of Machine Learning from the University of Southampton 2006. He is currently an Adjunct Faculty at School of Information Systems, Singapore Management University and an Honorary Senior Research Associate at the Centre for Computational Statistics & Machine Learning, University College London.
David regularly tutors, advises and provided consulting support in Analytics and Business Analytics. More can be found on www.davidroihardoon.com