Building good models only succeeds if you have a decent base table to start with. In this course you will learn how to construct a good base table, create variables and prepare your data for modeling. We finish with advanced topics on the matter.
In this chapter you will learn how to construct the foundations of your base table, namely the population and the target.
You will learn how to add variables to the base table that you can use to predict the target.
Once you derived variables from the raw data, it is time to clean the data and prepare it for modeling. In this Chapter we discuss the steps that need to be taken to make your data modeling-ready.
In some cases, the target or variables change heavily with the seasons. You will learn how you can deal with seasonality by adding different snapshots to the base table.
DatasetsDonor IDsBasetable with countries and ageBasetable used in Ex 2.13Living place of donorsDonations
PrerequisitesIntroduction to Predictive Analytics in Python
Data Scientist at Python Predictions
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