Mathematical Challenges in Machine Learning, Big Data Analytics and the Internet of Things
Lectures and seminars
Welcome to a guest lecture with George A Fodor, on Wednesday May 16.
Title: Mathematical Challenges in Machine Learning, Big Data Analytics and the Internet of Things
Speaker: George A Fodor , Q-TAGG R&D AB, Västerås, Sweden
Organized by: Division of Applied Mathematics, UKK, MDH
Most popular accounts on ML, BDA and IoT, are highlighting the technological and the magnitude challenges of these approaches. It is understood for instance that Big Data means a technological challenge of storing, processing and pipelining large quantities of data and that IoT posses an obvious computer network challenge. However, most technologies and theories used with these three approaches are not new. This rises questions about what makes the difference when some traditional technologies are increasing very much in their magnitude? A related question often asked by students in Mathematics, Engineering and Finance is if these three approaches use some kind of novel mathematics not taught before? What are the unsolved problems of this mathematics and more generally what kind of new systemic knowledge is needed to understand these new technologies at an appropriate abstraction level?
The presentation will introduce some answers to these questions by using intuitive real-life examples and explaining the related mathematical challenges in easy to understand terms.
This guest lecture is part of a series of open events organized in connection to the Bachelor’s and Master’s programmes in Financial Engineering and Engineering Mathematics offered by the Division of Applied Mathematics, School of Education, Culture and Communication, Mälardalen University. Events are aimed at students of mentioned programmes but are open to everyone interested at Mälardalen University. Purpose is inspiring and encouraging ongoing students in their pursuit of future carriers.