Typos and rephrasing in exercise 2

Module 1. The Predictive Modeling Pipeline Fitting a scikit-learn model on numerical data
#1

In exercise 02, Handling categorical data section.

The first question is to empirically evaluate whether scaling numerical feature is helpful or not;

I would have ended this sentence with a dot.

As in the previous notebooks, we use the utility make_column_selector to only select columns with a specific data type.

In referencing the pipeline, shouldn’t code cell:
print(f"The different scores obtained are: \n{scores}")
be replaced by
print(f"The different obtained scores are: \n{scores}")
?

And, in final hint:

You might want to use OneHotEncoder(handle_unknown="ignore", sparse=False) to force the use of a dense representation as a workaround.

#2

Fixed, thanks!

#3