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Feature engineering is as much of an art as it is a science. Requiring a deep knowledge of data sets and higher order data science skills, the process is often time consuming, error prone, hard to operationalize and worst case, results in poorly performing models.

With artificial intelligence becoming a key lever to competitive advantage and the growing use of machine learning to build predictive models, the importance of feature engineering continues to grow. Making this process more systematic and procedural can provide huge benefits to data science teams.

In this latest Data Science Central podcast, Anindya Datta, Mobilewalla CEO and Founder and a former professor of data science, discusses the current state of the art in feature engineering and the challenges data scientists face today in creating safe, drift resistant features.

Speaker:
Anindya Data Ph.D., CEO & Founder – Mobilewalla

Hosted by:
Sean Welch, Host and Producer - Data Science Central

Vendor:

Mobilewalla

Posted:

Sep 1, 2021

Premiered:

Aug 12, 2021

Format:

Video

Type:

Podcast