Before we dive into data munging, let's take a moment to explain the difference between an algorithm and a model, two terms we've been using up until now without a formal definition.
Consider the simple linear regression example we saw in Chapter 1, Introduction to Machine Learning and Predictive Analytics — the linear regression equation with one predictor:
Here, x is the variable, ŷ the prediction, not the real value, and (a,b) the parameters of the linear regression model:
- The conceptual or theoretical model is the representation of the data that is the most adapted to the actual dataset. It is chosen ...
