April 2022
Beginner to intermediate
200 pages
4h 15m
Korean
Content preview from MLOps 도입 가이드
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75
4장 모델개발
특성 저장소
특성 팩토리 혹은 특성 저장소
Feature
Store
는 기업체들과 관련된 여러 특성의 저장소
repository
다. 각
저장소는 손쉽게 재활용할 수 있도록 중앙에 저장한다. 보통 오프라인(다소 느리지만 더 강력함)
과 온라인(더 빠르고 실시간 대응에 유용함)으로 구성되어 있고, 상호 일관성을 유지한다.
데이터 과학자들이 특성 엔지니어링에 들여야 하는 시간을 감안하면, 특성 저장소는 데이터 과
학자들이 더 중요한 작업에 시간을 더 들일 수 있도록 하는 데 큰 도움이 될 수 있다. 머신러닝은
여전히 ‘기술 부채와 관련된 고금리 신용카드(
https://oreil.ly/IYXUi
)’와 같다. 기술 부채를
탕감하려면 데이터-모델-상용화로 이어지는 절차와
MLOps
프로세스를 엄청나게 효율화해야
한다. 특성 저장소는 그 방법 중 하나가 될 수 있다.
결론적으로, 모델을 구축할 때 특성 엔지니어링 및 특성 선택 과정이란 머신러닝 모델의 다른
구성 요소와 마찬가지로
MLOps
구성 요소와 성능 사이의 미묘한 균형을 찾는 것이다.
4.4
실험
실험은 모델 개발 프로세스 전체에 걸쳐 수행된다. 보통 모든 중요한 결정이나 가정을 증명하
기 위한 실험 혹은 연구를 기반으로 한다. 실험은 완전한 머신러닝 예측 모델 구축에서부터 통
계적 테스트 혹은 ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.