Alex is a 3rd Year Student at Edinburgh University and a part time software developer with LiveCode. His experience with Machine Learning comes from a couple of applied courses at University, in addition to briefly using Machine Learning concepts and libraries during his internship at Bloomberg LP in London, during the summer of 2017. He is interested in all areas of informatics, but his focus lies with low level development in C++ and the theory of programming languages.

Nowadays, Machine Learning is taking up a very important role within all Computer Science communities, and it has the potential to outgrow this area by a lot. At the moment, the de facto standard for doing Machine Learning is using NumPy & Co. in the Python world. Whilst for people with a strong background in CS Python represents a very easy way of developing new software fast, programmers who believe in the philosophy and ease of use of LiveCode would probably be discouraged by its many quirks and verbosity. As such, we propose a proof of concept, defining a simple library in LiveCode, that lets users develop quick Machine Learning Models, allowing them to combine the power of complex mathematical models with the ease of coding in LiveCode. Topics covered will include : statistical analysis, linear and logistic regression and basic data visualisation.

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