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 ...