Explainability, privacy, and sustainability in feature stores
In Chapter 10, we introduced the concept of feature stores and demonstrated with an example how online feature stores can be used. Furthermore, in the previous section, we learned about the important aspects of sustainable model training and deployment and the best practices for tracking sustainable model metrics across different cloud providers. We also saw in Chapter 12 that FL provides a training environment to allow sustainability, by allowing the local training of devices. Hence, we must try to leverage FL in training ML models in healthcare, retail, banking, and other industry verticals in scenarios where generic model representation plays an important role as computational power is limited.
In this section, let’s dig deeper into creating explainable, private, and sustainable feature stores.
Feature store components and functionalities
Let’s now explore how the different components of a feature...