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Using Feature Stores for Managing Feature Engineering in Python

Key Takeaways:
  • Learn best practices for engineering features for machine learning.
  • Learn why, how and when to reuse features between machine learning projects.
  • Learn how to get started using a feature store.
Tuesday August 8, 11AM ET
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Feature engineering is one of the most important steps in machine learning - it's how you improve the predictive performance of your models. In a corporate setting, one underappreciated problem is that you don't want to reinvent your feature engineering work in every project. To solve this, you need a way to reuse features from one project to the next.

In this live training, Colin teaches you how to manage the features for your machine learning models, to save you time and improve the consistency of your models.

Presenter Bio

Colin Priest Headshot
Colin PriestChief Evangelist at FeatureByte

As Chief Evangelist at FeatureByte, Colin helps organizations manage feature engineering processes. He is an expert in digital transformation, data strategy, and automating data processes. He was previously Global Lead for AI Governance at DataRobot and Chief Technology Officer at IntelliM.

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