January 2017
Beginner to intermediate
312 pages
7h 3m
Korean
Content preview from 밑바닥부터 시작하는 딥러닝
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141
4
장
-
신경망 학습
다. 이 메서드는
predict
( )의 결과와 정답 레이블을 바탕으로 교차 엔트로피 오차를 구하도록
구현했습니다.
남은
numerical
_
gradient
(
self
,
x
,
t
) 메서드는 각 매개변수의 기울기를 계산합니다. 수치 미
분 방식으로 각 매개변수의 손실 함수에 대한 기울기를 계산하죠. 마지막
gradient
(
self
,
x
,
t
)
는 다음 장에서 구현할 메서드입니다. 이 메서드는 오차역전파법을 사용하여 기울기를 효율적
이고 빠르게 계산합니다.
numerical
_
gradient
(
self
,
x
,
t
)는 수치 미분 방식으로 매개변수의 기울기를 계산합니다. 다음 장
에서는 이 기울기 계산을 고속으로 수행하는 기법을 설명합니다. 그 방법은 바로 오차역전파법입니다. 오차역
전파법을 쓰면 수치 미분을 사용할 때와 거의 같은 결과를 훨씬 빠르게 얻을 수 있죠. 오차역전파법으로 기울
기를 구하는
gradient
(
self
,
x
,
t
) 메서드는 다음 장에서 구현합니다. 신경망 학습은 시간이 오래 걸리니, 시
간을 절약하려면
numerical
_
gradient
(
self
,
x
,
t
) 대신
gradient
(
self
,
x
,
t
)을 쓰는 것이 좋습니다!
4.5.2
미니배치 학습 구현하기
신경망 학습 구현에는 앞에서 설명한 미니배치 학습을 활용하겠습니다. 미니배치 ...
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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.