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잘되는 머신러닝 팀엔 이유가 있다
book

잘되는 머신러닝 팀엔 이유가 있다

by 데이비드 탄, 에이다 양, 데이비드 콜스, 라인 AI Lab
June 2025
Beginner to intermediate
484 pages
10h 52m
Korean
Hanbit Media, Inc.
Content preview from 잘되는 머신러닝 팀엔 이유가 있다
334
Part 2
엔지니어링
이 줄은 너무 많은 구현 세부 사항을 드러내고, 코드를 읽고 이해하기 어렵게 만듭니다.
다음으로 단위 테스트를 작성한 뒤 실패하는 것을 확인해 봅시다.
deftest_add_is_alone_column():
  df=pd.DataFrame({
       'SibSp':[0,1,2,0,0],
       'Parch':[0,0,5,0,1]
  })
  expected=pd.DataFrame({
       'SibSp':[0,1,2,0,0],
       'Parch':[0,0,5,0,1],
       'IsAlone':[1,0,0,1,0]
  })
  assert_frame_equal(expected,add_is_alone_column(df))
주로 새 테스트는 실패해야 합니다. 다음 단계에서는 ‘메서드 추출’ 리팩터링 단축키를 적용
하여 이 로직을 새 함수인
add
_
is
_
alone
_
column
()
로 추출합니다. 이 새 함수를 가져와서
모든 테스트가 통과하는지 확인하고, 변경 사항을 커밋합니다. 다시 한번 만세!
8.2.3
우리가 이룬 것을 돌아보기
리팩터링 주기를 몇 번 더 반복하고 나서, 우리는 코드베이스를 모듈화되고, 읽기 쉽고, 테스
트된 상태로 만들었습니다. ...
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Publisher Resources

ISBN: 9791169213875