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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171
7
장
모델 분석 및 검증
다음 절에서는 텐서플로에서 공정성을 평가할 때
TFMA
, 공정성 지표,
What
-
If
Tool
프로젝
트를 사용하는 방법을 설명합니다.
7.3.1
TFMA
에서 슬라이싱 모델 예측 수행하기
머신러닝 모델의 공정성을 평가하는 첫 번째 단계는 관심 있는 그룹 (예: 성별, 인종, 국가)별
로 모델의 예측을 잘라내는 것입니다. 이런 슬라이스
slice
는
TFMA
나 공정성 지표 도구로 생성
할 수 있습니다.
TFMA
에서 분할하려면 슬라이스 열을
SliceSpec
으로 제공해야 합니다. 이
예에서는
Product
피처를 살펴보겠습니다.
slices = [tfma.slicer.SingleSliceSpec(),
tfma.slicer.SingleSliceSpec(columns=[‘Product’])]
지정된 인수가 없는
SingleSliceSpec
은 전체 데이터셋을 반환합니다.
그런 다음 지정된 슬라이스로 모델 분석 단계를 실행합니다.
eval_result = tfma.run_model_analysis(
eval_shared_model=eval_shared_model,
eval_config=eval_config_viz,
data_location=_EVAL_DATA_FILE,
output_path=_EVAL_RESULT_LOCATION,
file_format=’tfrecords’, ...
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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.