September 2023
Beginner to intermediate
1044 pages
27h 52m
Korean
Content preview from 핸즈온 머신러닝(3판)
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641
15
장
RNN과 CNN을 사용한 시퀀스 처리
망도 실제로 잘 작동할 수 있습니다. 이 두 가능성을 살펴본 뒤 마지막에
WaveNet
을 구현하겠
습니다. 이 네트워크는 수만 개의 타임 스텝을 가진 시퀀스를 다룰 수 있는
CNN
구조입니다.
그럼 시작해봅시다.
15.1
순환 뉴런과 순환 층
지금까지는 활성화 신호가 입력 층에서 출력 층 방향으로만 흐르는 피드포워드 신경망에 초점
을 맞추었습니다. 순환 신경망은 피드포워드 신경망과 매우 비슷하지만 뒤쪽으로 순환하는 연
결도 있다는 점이 다릅니다.
[그림
15
-
1
]의 왼쪽 그림처럼 입력을 받아 출력을 만들고 자신에게도 출력을 보내는 뉴런 하
나로 구성된 가장 간단한
RNN
을 살펴봅시다. 각
타임
스텝
time
step
t
(또는
프레임
frame
)마다 이
순환
뉴런
recurrent
neuron
은
x
(
t
)
와 이전 타임 스텝의 출력인
ŷ
(t
-
1 )
을 입력으로 받습니다. 첫 번째 타
임 스텝에서는 이전 출력이 없으므로 일반적으로
0
으로 설정됩니다. 이 작은 네트워크를 [그림
15
-
1
] 오른쪽 그림처럼 시간을 축으로 하여 표현할 수 있는데 이를
시간에
따라
네트워크를
펼
쳤다
unrolling
the
network
through
time
고 말합니다(동일한 뉴런을 타임 스텝마다 하나씩 표현한 것입니
다).
Time
x
(0)
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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.