This is the third installment in a three-part series about machine learning. In this blog, well focus on metrics that are used to evaluate algorithms applied to supervised machine learning (ML) Algorithm or Regression is used when the target variable is a number. In the next section, we’ll be looking at the various metrics for each, Classification, Regression, which can help us determine the efficacy of our chosen ML model. The main difference between the two is that the output variable in Regression is numerical while he output for Classification is categorical/discrete.”]