The first part of the workshop will cover the basics of feature engineering, including the different types of features, the importance of feature selection, and the different techniques for feature transformation.

The second part of the workshop will focus on the application of feature engineering to real-world data sets. Attendees will learn how to identify the key challenges in feature engineering and how to select the right feature engineering techniques for their data set.

The final part of the workshop will be a hands-on exercise where attendees will apply feature engineering to a real-world data set. This exercise will give attendees the opportunity to practice the skills they have learned throughout the workshop.

This session is an intermediate level session and is ideal for data scientists, machine learning engineers, and anyone interested in learning more about feature engineering.

After the session, attendees will be able to identify the key challenges in feature engineering, select the right feature engineering techniques for their data set, and implement feature engineering in their machine learning projects.