AHL Explains

In the third chapter of the series, Anthony explores some of the different areas within the hybrid discipline of Machine Learning. He uses an example binary classification problem to illustrate the differences between traditional Linear and Empirical approaches and a Bayesian Machine Learning classifier, noting the advantages and weaknesses inherent to each method.

Released on 04 October 2016

AHL Explains Series

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