April 2022
Beginner to intermediate
200 pages
4h 15m
Korean
Content preview from MLOps 도입 가이드
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1
부에서는
MLOps
라는 주제를 전반적으로 소개한다.
MLOps
가 어떻게 그리고 어떤 이유에
서 원칙
discipline
이 되었는지,
MLOps
를 성공적으로 실행하려면 어떤 사람들이
MLOps
에 참여
해야 하는지, 그리고 어떤 구성 요소가 있는지를 설명하였다.
2
부는 머신러닝 모델 생애주기에 맞춰 모델 개발, 상용화 준비, 상용 환경 배포, 모니터링과 피
드백 루프, 모델 거버넌스
Governance
등의 순서로 구성하였다. 각 장에서는 일반적인 고려 사항과
함께
MLOps
관련 고려 사항을 다루었다. 특히,
1
부
3
장에서 가볍게 소개한 주제들을 상세하
게 설명한다.
3
부에서는 오늘날 기업에서 운영하는
MLOps
의 모습에 대한 실질적 예시를 제공하여, 독자들
이 실제 구축 형태와 그 의미를 이해할 수 있도록 하였다. 등장하는 회사명은 모두 가명이지만,
모든 사례는 실제 기업에서
MLOps
와 모델 관리에 대해 겪고 있는 경험을 바탕으로 구성하였
다.
서문
10
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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.