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Using Feature Stores for Managing Feature Engineering in Python


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.

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.

Also, make sure to sign up to Featurbyte to generate your own API Token

Feature Engineering for Machine Learning in Python

Preprocessing for Machine Learning in Python

MLOps Fundamentals

The Machine Learning Workflow

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Colin Priest Headshot
Colin Priest

Chief Evangelist at FeatureByte

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