Presentation Slides: Machine Learning, Predictive Modelling, and Pattern Recognition in Business Analytics

I recently delivered a presentation entitled “Using Advanced Predictive Modelling and Pattern Recognition in Business Analytics” at the Statistical Society of Canada’s (SSC’s) Southern Ontario Regional Association (SORA) Business Analytics Seminar Series.  In this presentation, I

– discussed how traditional statistical techniques often fail in analyzing large data sets

– defined and described machine learning, supervised learning, unsupervised learning, and the many classes of techniques within these fields, as well as common examples in business analytics to illustrate these concepts

– introduced partial least squares regression and bootstrap forest (or random forest) as two examples of supervised learning (0r predictive modelling) techniques that can effectively overcome the common failures of traditional statistical techniques and can be easily implemented in JMP

– illustrated how partial least squares regression and bootstrap forest were successfully used to solve some major problems for 2 different clients at Predictum, where I currently work as a statistician

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