학술논문
Feature Stores: A Key Enabler for Feature Reusability and Availability Across Machine Learning Pipelines
Document Type
Periodical
Author
Source
Computer. 57(1):69-74 Jan, 2024
Subject
Language
ISSN
0018-9162
1558-0814
1558-0814
Abstract
This article presents a technical analysis of the feature store (FS) from the perspective of machine learning (ML) model development and highlights its potential benefits. We propose key considerations in developing a workable and efficient FS for ML pipelines.