Feature Engineering: What It Is and How to Leverage It in Data Science

Learn what feature engineering, what the process looks like, and ways that data scientists can improve this process ‚ö°




Abstract: Predictive modeling success hinges on selecting the features that are most likely to affect the desired outcome and sub-optimal featuring engineering is one of the culprits behind poorly performing models. Today more art than science, feature engineering is a difficult process even for the most experienced data scientist.

In this session, we will discuss:

What is feature engineering and what does the process look like

Where does feature engineering fit in the machine learning life cycle

The importance of data pipelines in feature selection

The downstream modeling impacts of feature selection

Ways that data scientists can improve this process

The event is finished.


May 12 2022


7:00 pm - 8:00 pm

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