J Feature Store for Machine Learning

Curate, discover, share and serve ML features at scale
1. Auflage 2022
ISBN: 978-1-80324-598-0
Verlag: De Gruyter
Format: EPUB
Kopierschutz: 0 - No protection

E-Book, Englisch, 280 Seiten

No detailed description available for "Feature Store for Machine Learning".

Autoren/Hrsg.

J, Jayanth Kumar M

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Informationsarchitektur
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Datenbankdesign & Datenbanktheorie
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Automatische Datenerfassung, Datenanalyse

Inhaltsverzeichnis

Table of Contents - An Overview of the Machine Learning Life Cycle
- What Problems Do Feature Stores Solve?
- Feature Store Fundamentals, Terminology, and Usage
- Adding Feature Store to ML Models
- Model Training and Inference
- Model to Production and Beyond
- Feast Alternatives and ML Best Practices
- Use Case – Customer Churn Prediction

Über Autor(innen)

J Jayanth Kumar M:

Jayanth Kumar M J is a Lead Data engineer at Cimpress USA. He specializes in building platform components for data scientists and data engineers to make MLops smooth and self-service. He is also a Feast feature store contributor.