In most events or conversations that address machine learning there is a tendency for the matter to mostly be addressed from a distance; in the sense that we mostly discuss the implications of machine learning or deviate into what it will look like once the robots decide to conquer the world. Both of these things are very interesting but it also means that up until now, many of us won’t have had the chance to see how a machine learning algorithms actually work. So in this seminar we did finally get a chance to see how some of these things worked. We looked at: fitting data via regression, regression with non-linear functions, and feed forward neural networks. Many of these concepts were new to us but they were all delivered in a clear and efficient manner.
By Jacob Hammers
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