hosted by Peter Elger & Keelin Murphy
As is customary at these occasions, exquisite craft beer and pizza was offered to all attendees!
Prof. Paul Walsh has a PhD in Computer Science. He is a director of the SIGMA research group which is based at Cork Institute of Technology. SIGMA focuses on applying machine learning to real-world problems, and Paul has a keen interest in solving problems in health-care and life science. He is an experienced machine learning technology expert having published over 80 articles & book chapters on the subject. Paul has consulted with industry on the topic of machine learning, and has founded several start-ups, including life science software company http://www.nsilico.com which uses machine learning to analyze genomic and biomedical data. He is the principal investigator for major national and international research programs, including SFI and H2020, and is a certified technology and project management professional with experience in consultancy for major international clients.
A Support Vector Machine (SVM) is a supervised machine learning algorithm that can be employed for both classification and regression purposes. SVMs are more commonly used in classification problems and are based on the concept of finding a hyperplane that best divides a data set into two classes. Support vectors are the data points nearest to the hyperplane; the points of a data set that, if removed, would alter the position of the dividing hyperplane. Because of this, they can be considered the critical elements of a data set.
When there is no clear hyperplane it is difficult to divide a dataset into two classes. This is where the Kernel Trick comes into play by adding an extra dimension, like in the image below, you can then more easily identify a hyperplane.
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Paul’s presentation slides from the meetup -Download
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