October 2021
Beginner to intermediate
416 pages
9h 3m
Korean
Content preview from 살아 움직이는 머신러닝 파이프라인 설계: 텐서플로와 함께하는 머신러닝 프로젝트 자동화
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63
3
장
데이터 수집
이 장에서는 기본
TFX
설정과
ML
메타데이터스토어를 사용하여 데이터셋을 다양한 컴포넌트
에서 활용할 수 있도록 파이프라인으로 데이터를 수집하는 방법을 중점적으로 다룹니다. [그림
3
-
1
]처럼 말이죠.
데이터
수집
파이프라인
오케스트레이션
메타데이터스토어 데이터베이스
데이터
검증
데이터
전처리
모델 피드백 루프
모델
학습
모델 분석 및
검증
모델
배포
그림
3-1
머신러닝 파이프라인의 일부인 데이터 수집
TFX
는 파일이나 서비스에서 데이터를 수집하는 컴포넌트를 제공합니다. 이 장에서는 기본 개
념을 개괄적으로 살펴보고, 데이터셋을 학습 및 평가 하위 집합으로 분할하는 방법을 설명합니
다. 또한 추출된 여러 데이터를 하나의 포괄적인 데이터셋으로 결합하는 방법을 시연합니다.
그런 다음 이전 사용 사례에서 유용함이 입증된 다양한 형태의 데이터 (정형 데이터, 텍스트,
이미지 )를 수집하는 몇 가지 전략을 논의합니다.
데이터 수집
CHAPTER
3
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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.
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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.