Before model building, you first need to perform the test-train split and scale the features.
Scaling of variables is an important step because, as you may have noticed, the variable ‘area’ is on a different scale with respect to all other numerical variables, which take very small values. Also, the categorical variables that you encoded earlier take either 0 or 1 as their values. Hence, it is important to have everything on the same scale for the model to be easily interpretable.
In the next video, let’s continue with the data preparation process before modelling it.
Now that you have prepared the data and are done with the test-train split, let’s prepare a heat map and take a look at the correlations between the variables.
Coming up
In the next segment, you will start building a multiple linear regression model to predict values based on multiple variables, instead of a single one.