Feature Stores
Design and operate feature stores for consistent training and serving features.
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After this skill you can…
- Define feature views in Feast
- Serve features with low latency for online inference
- Avoid training-serving skew with a unified feature store
Prerequisites
Watch (10 videos)
Using Feature Stores for Managing Feature Engineering in Python
→ Implement feature stores→ Use feature stores for machine learning
Global Feature Store // Gottam Sai Bharath & Cole Bailey // MLOps Podcast #263
→ Design a Global Feature Store→ Implement MLOps practices for feature engineering
Feast Feature Store Deep Dive // Felix Wang // MLOps Meetup #81
→ Implement a feature store with Feast→ Use a feature store for data management
Get Data Into Databricks - Feature Store
→ Create and Manage Features→ Discover and Reuse Features→ Integrate Features into Client Applications
Context Engineering 2.0
→ Design feature stores for AI→ Implement context engineering for agents
Feature Stores for MLOps with Mike del Balso - #420
→ Build a feature store→ Operationalize machine learning→ Integrate feature store with MLOps infrastructure
Feature Engineering
→ Use BigQuery ML for feature engineering→ Develop ML models with Keras and TensorFlow
Feature Stores at Shopify and Skyscanner // Matt Delacour and Mike Moran // Reading Group #4
→ Implement Feature Stores→ Manage machine learning data
Unpacking 3 Types of Feature Stores // Simba Khadder // MLOps Podcast #265
→ Implement feature stores in MLOps→ Use vector stores for machine learning
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