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
Get Data Into Databricks - Feature Store
→ Create and Manage Features→ Discover and Reuse Features→ Integrate Features into Client Applications
Feature Stores for MLOps with Mike del Balso - #420
→ Build a feature store→ Operationalize machine learning→ Integrate feature store with MLOps infrastructure
Unpacking 3 Types of Feature Stores // Simba Khadder // MLOps Podcast #265
→ Design Feature Stores→ Implement Feature Stores→ Optimize Feature Stores
Global Feature Store // Gottam Sai Bharath & Cole Bailey // MLOps Podcast #263
→ Create micro feature stores→ Unify feature stores into a Global Feature Store
Unifying Systems with Uber’s Michelangelo Platform // MLOps Podcast #239 clip
→ Design and implement feature stores→ Manage and maintain feature stores
Do You Really Need a Feature Store
→ Design a Feature Store→ Implement a Feature Store→ Optimize Feature Store Performance
The Future of Feature Stores and Platforms // Mike Del Balso & Josh Wills // MLOps Podcast # 186
→ Design Feature Stores→ Implement Feature Sharing→ Create Templates for Feature Engineering
🚀 Real-Time Feature Store Demo | Deploy an End-to-End MLOps Pipeline with Feast + Redis + Streamlit
→ Build a feature store→ Manage features→ Use features for modeling
Feast Feature Store Deep Dive // Felix Wang // MLOps Meetup #81
→ Implement a feature store with Feast→ Use a feature store for data management
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