September 2024
Beginner to intermediate
364 pages
8h 27m
Korean
Content preview from 머신러닝 인터뷰 실무 가이드
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120
머신러닝 인터뷰 실무 가이드
정규화는 모델의 분산을 줄일 수 있지만, 의도치 않게 편향을 증가시킬 수 있으므로 다양한 모델 개선 기법을
시험하며 신중해야 합니다.
기초적인 기법에 관한 인터뷰 문제 예제
이제 다양한 통계 및 머신러닝 기법들을 상위 수준에서 다루었으니, 몇 가지 인터뷰 문제 예
제를 살펴보겠습니다. 여기에서는 이번 절에서 다룬 개념에서 파생된 일반적인 인터뷰 문제
들의 세부 사항을 깊이 다루겠습니다. 이전에 다루지 않았던 세부 사항들도 있을 수 있으므
로, 이러한 예시 문제들이 새로운 개념을 이해하는 데 도움이 되기를 바랍니다.
인터뷰 문제
3
-
1
:
L1
정규화와
L2
정규화는 무엇인가요?
답변 예시
L1
정규화 또는 라쏘 정규화
lasso
regularization
12
라고도 불리는 이 정규화 방법은 모델 파라미터를
0
을 향해 축소시켜 나갑니다.
L2
정규화 (또는 릿지 정규화
ridge
regularization
)는 목적 함수에 모
델 계수의 제곱에 비례하는 패널티 항을 추가합니다. 이 패널티 항은 계수를
0
의 방향으로 축
소시켜 나가지만,
L1
(라쏘 ) 정규화와는 달리 계수를 정확히
0
으로 만들지는 않습니다.
L2
정
규화는 계수가 너무 커지는 것을 방지함으로써 과적합을 줄이고 모델의 안정성을 개선하는
데 도움을 줄 수 있습니다.
L1 ...
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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.