Presenters: Nicolas Attilades

Level: Foundation

CPD: 6 hours

This is a one day course covering the application of machine learning methodology to real world analytics problems. The course outlines the stages involved in a machine learning analysis, and walks through how to perform them using the R programming language and the caret library.  Participants will be provided with exercises to complete in R so as to gain hands on experience in using the methods presented. 

The individual stages of: problem formulation, data preparation, feature engineering, model selection and model refinement will be walked through in detail giving participants a solid process to follow for any machine learning analysis. This includes methods for evaluating machine learning models in terms of a performance metric as well as assessing bias and variance.

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