The Importance of Good Data (and a good data model!)

ML largely relies on data sets in order to build the model. If you train a model off of bad data, or data that doesn't take into consdieration various nuances you could set yourself up for not only inaccurate results — but also problematic results through misinterpreting different segments of the world.

How to select data for modeling#

Selecting data for modeling can appear overwhelming at first. The first thing to do is to approach the situation with an understanding of what you are asking.

Tackling your first dataset#

When you approach a dataset — you'll need to look at all of the different columns in the dataset. Use the columns property of the DataFrame in order to do so.

input

melbourne_file_path = '../input/melbourne-housing-snapshot/melb_data.csv' melbourne_data = pd.read_csv(melbourne_file_path) melbourne_data.columns