April 2022
Beginner to intermediate
200 pages
4h 15m
Korean
Content preview from MLOps 도입 가이드
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174
3부MLOps실제사례
류의 특정 인식을 테스트하기 위한 실험을 수립하기도 어려웠으며, 고객 행동 변화에 따라 규
칙을 갱신하기도 어려웠다.
10.1.1
머신러닝의 역할
머신러닝의 부상은 추천 엔진에 새로운 패러다임을 가져왔고 인간의 통찰력에 기반한 규칙은
사라지게 되었다. 협업 필터링
collaborative
filtering
이라고 불리는 새로운 종류의 알고리즘이 이 분야
를 지배하고 있다. 이 알고리즘은 사전 마케팅 지식 없이도 수백만 명의 고객과 수만 개의 제품
에 대한 고객 및 데이터를 분석하여 추천을 수행할 수 있는 알고리즘이다. 마케팅 담당자는 어
떤 고객과 유사한 고객들을 효율적으로 파악함으로써 비용과 효율성 면에서 기존 방식을 능가
하는 자동적인 전략을 활용할 수 있다.
전략을 수립하는 과정이 자동적이기 때문에, 정기적으로 전략을 업데이트할 수 있고
A
/
B
테
스트나 섀도우 스코어링(모든 가능성 중 특정 인식을 선택하는 방법 포함) 방식을 활용하여 전
략 간에 비교할 수 있다. 이러한 알고리즘은 다양한 이유로 고전적인 비즈니스 규칙과 결합할
수 있다. 예를 들면, 필터링 버블
filtering
bubble
1
을 방지하거나 특정 지역에서 제품 판매를 금지하
거나 통계적으로 의미가 있으나 비윤리적인 사용(예를 들어, 알코올 중독 회복자에게 알코올을 ...
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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.