Intermediate Predictive Analytics in Python

Learn how to prepare and organize your data for predictive analytics.

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.

• Crucial base table concepts
• In this chapter you will learn how to construct the foundations of your base table, namely the population and the target.
• Creating variables
• You will learn how to add variables to the base table that you can use to predict the target.
• Data preparation
• 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.
• Advanced base table concepts
• 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.