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Feature Engineering and Selection: A Practical Approach for Predictive Models

The goals of Feature Engineering and Selection are to provide tools for re-representing predictors, to place these tools in the context of a good predictive modeling framework, and to convey our experience of utilizing these tools in practice. In the end, we hope that these tools and our experience will help you generate better models.

Created by Max Kuhn and Kjell Johnson


What you’ll learn

Through this educational resource you can acquire the compentencies demanded from companies today. The most in demand technique from the educational resource that is frequently mentioned by organizations is Data Modeling.

Who will benefit?

Mapping the description from this learning opportunity with nearly 10,000 data-related job postings, we find that those interested in Data Scientist roles would benefit the most.