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Webinar February 4: Selecting Target Variables in Modeling

Community Team
Community Team
2 2 482

(Part of a data modeling webinar series.)

Many people who are new to data science struggle with the preparation of the data. This is not surprising, given the many tutorials available on how to build models using already prepared data (think: Kaggle).

In this webinar, we spend some time exploring an important piece that is often missing: creating the target variable.

Hosts

  • Lukas Innig (DataRobot, Customer Facing Data Scientist)
  • Rajiv Shah (DataRobot, Customer Facing Data Scientist)

Now what? 

After watching the webinar, you should check out more information about target selection and preparing data.

Questions?

Also, if you have comments or questions that weren't answered in the webinar, click Comment (below) and post them now.

2 Comments
Computer Board

Great video since this is an important topic in data science that isn't common spoken about. 

The customer churn example reminded me a lot of this blog post: https://blog.featurelabs.com/prediction-engineering-churn/.

They have a similar diagram to the ones you show in the video.

churn.png

 

Do you know of any other resources or tools that deal with this of prediction engineering? 

Data Scientist
Data Scientist
Hi Joe, thank you for your interest in this. There is some more information specifically on Churn prediction here: https://blog.datarobot.com/predicting-churn-how-data-can-help-with-customer-retention Other than that, I can recommend the TWIML podcast. They had an episode on these types of challenges in ML recently: https://twimlai.com/twiml-talk-349-turning-ideas-into-ml-powered-products-with-emmanuel-ameisen/ Cheers, Lukas
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About the Author
Linda is Senior Technical Writer for DataRobot Community.