Response: 

We perform different EXPLORATION tasks when we get input datasets to perform analyses and understand the same. Once our data is ready and analyzed, we try to perform the FEATURE engineering process to make it ready to be used in a modelling process. 

Feature engineering process comprises of two key tasks such as Variable/feature transformation and Variable/feature creation. 

Variable or feature transformation – This is where a variable is replaced by a function. For example, replacing a variable F1 by the square or CUBE root or logarithm F1 is a transformation. Therefore, this process changes the distribution or relationship of a variable with others. 

Some of the SITUATIONS where we want to use variable transformation are as follows: 

1. For standardization purposes or scale-up cases – if it is needed to change the scale of the variable or to standardize it for better interpretation. While transformation is important, it does not necessarily change the shape of a variable distribution. 
2. For transforming non-linear to linear relationships – if it is needed to transform non-linear relationships into linear relationships, then this may be used. Linear relationship between variables is simpler to interpret compared to a non-linear relation. Some examples are - Scatter plots, Log transformation approaches. These techniques can be used as different techniques in these situations.