August 2021
Beginner to intermediate
720 pages
15h 32m
Korean
Content preview from fastai와 파이토치가 만나 꽃피운 딥러닝
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605
16
학습 과정
16.5
Adam
Adam
은 모멘텀을 적용한
SGD
와
RMSProp
을 함께 고려한 방식입니다. 그레이디언트의 이
동평균으로 방향성을 정하고, 그레이디언트 제곱에 대한 이동평균의 제곱근으로 나눠 파라미
터별로 적응형 학습률을 제공합니다.
Adam
은 비편향
unbiased
이동평균을 취한다는 점에서 약간 다른 방식으로 이동평균을 계산합니
다. 다음은
i
번째 반복에서 계산된 불편 이동평균의 계산식입니다(
0
부터 시작 ).
w.avg = beta * w.avg + (1-beta) * w.grad
unbias_avg = w.avg / (1 - (beta**(i+1)))
나누는 수
1
- (
beta
**(
i
+
1
))
은 불편 이동평균이 초기의 그레이디언트처럼 보이게 합니다
(
beta
가
1
보다 작아서 분모는 빠르게
1
에 가까워집니다 ).
모든 내용을 종합하면 아래와 같은 가중치 갱신 단계 코드를 만들 수 있습니다.
w.avg = beta1 * w.avg + (1-beta1) * w.grad
unbias_avg = w.avg / (1
- (beta1**(i+1)))
w.sqr_avg = beta2 * w.sqr_avg + (1-beta2) * (w.grad ** 2)
new_w = w - lr * unbias_avg / sqrt(w.sqr_avg + eps)
eps
는 ...
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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.