March 2026
Intermediate
504 pages
11h 26m
Korean
Content preview from 파이토치로 배우는 LLM & AI
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308
1
부
모델 구축
값
타임 스텝
검증 실젯값
검증 예측값
그림
11-13
100
일 치 데이터에 대한 예측값과 실젯값
예측 곡선이 대체적으로 데이터를 따라가고 트렌드를 정확하게 예측하고 있지만, 특히 양극단
에서 상당히 간격이 벌어져 있으므로 개선할 여지가 있습니다.
데이터를 정규화했기 때문에 손실과
MAE
가 낮아 보일 수 있습니다. 실제보다 훨씬 분산이 낮
은 정규화된 값의 손실과
MAE
이기 때문입니다. 따라서 [그림
11
-
14
]에서 보듯이 작은 손실
값은 오해를 일으킬 수 있습니다.
훈련 손실
검증 손실
손실
에폭
그림
11-14
KNMI
데이터의 훈련 손실과 검증 손실
원본 데이터로 복원하기 위해 정규화를 거꾸로 적용할 수 있습니다. 먼저 표준편차를 곱하고
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and much more.
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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.