Machine learning theory and practice – CVB, Halcon and more
Machine learning is a branch of AI that covers deep learning and more – teaching classifiers by example rather than by parameterisation. This course covers the theory of convolutional neural networks (CNNs, aka Deep Learning) and some of the alternatives including Support Vector Machines and Ridge Regression.
The aim is not to be a softwareheavy training course, but to give the attendees the confidence to try machine learning in their own applications, by working through training strategies and the process of creating a successful machine learning solution. By using practical examples and training on real data, the attendee will become comfortable with the different approach that machine learning demands.
The intention is to give the attendee a feeling for the differences and similarities of the various approaches so that they can make an informed decision about whether machine learning is appropriate for a given problem and how they might approach it.