August 2021
Beginner to intermediate
720 pages
15h 32m
Korean
Content preview from fastai와 파이토치가 만나 꽃피운 딥러닝
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326
2
fastai 애플리케이션 계층 이해하기
하는 이유입니다. 따라서
SGD
의 갱신 단계도 제한됩니다. ‘모델의 적응 능력을 감소시킨다’는
말은 전이 학습에서 갱신이 어렵다는 의미입니다. 이는 잘못된 예측에서 비롯한 손실의 차이에
는 제한이 없지만, 매번 제한된 단계만 나아갈 수 있기 때문입니다.
레이블 평활화를 실제로 사용하려면
Learner
생성 시 손실 함수 부분만 바꿔주면 됩니다.
model = xresnet50(n_out=dls.c)
learn = Learner(dls, model, loss_func=LabelSmoothingCrossEntropy(),
metrics=accuracy)
learn.fit_one_cycle(5, 3e-3)
믹스업과 마찬가지로 더 많은 에포크 동안 학습을 진행하지 않는 한, 레이블 평활화로는 보통
크게 개선되기 어렵습니다. 여러분 스스로 시도해보고 이유를 생각해보기 바랍니다. 레이블 평
활화로 개선이 이뤄지기까지 얼마나 많은 에포크의 학습을 진행해야 할까요?
7.7
지금까지 영상 처리의 최신 모델 학습에 필요한 내용을 모두 배웠습니다. 직접 구현한 적도 있
고 전이 학습을 사용하기도 했죠. 이제 배운 내용을 여러분만의 문제에 적용하고 실험해보세
요. 믹스업과 함께 레이블 평활화를 사용하거나, 둘 중 하나만 사용해서 ...
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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.