Feature Store for Machine Learning

Chapter 3: Feature Store Fundamentals, Terminology, and Usage

In the last chapter, we discussed the need to bring features into production and different ways of doing so, along with a look at common issues with these approaches and how feature stores can solve them. We have built up a lot of expectations about feature stores, and it's time to understand how they work. As mentioned in the last chapter, a feature store is different from a traditional database – it is a data storage service for managing machine learning features, a hybrid system that can be used for storage and retrieval of historical features for model training. It can also serve the latest features at low latency for real-time prediction, and at sub-second latency for batch ...