August 2022
Beginner to intermediate
464 pages
10h 42m
Korean
Content preview from 개발자를 위한 머신러닝&딥러닝
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188
1
부
모델 구축
[그림
7
-
5
]처럼 순환 뉴런을 타임 스텝에 걸쳐 나란히 나열하면 작동 방식이 조금 더 명확해집
니다.
3
그림
7-5
타임 스텝에 걸쳐 펼친 순환 뉴런
여기에서
x
0
를 연산에 사용해
y
0
와 다음 타임 스텝으로 전달되는 값을 얻습니다. 다음 스텝에서
이 값과
x
1
을 받아
y
1
과 다음 타임 스텝으로 전달되는 값을 만듭니다. 그다음 스텝은 이 값과
x
2
를 받아
y
2
와 다음 타임 스텝으로 전달되는 값을 만드는 방식으로 계속 진행됩니다. 피보나치
수열과 진행 과정이 매우 유사하므로
RNN
의 작동 방식을 기억할 때 피보나치 수열을 연상하
면 쉽게 떠올릴 수 있을 겁니다.
7.2
순환을 언어로 확장하기
이전 절에서 여러 타임 스텝에 걸쳐 순환 신경망이 시퀀스의 문맥을 유지하는 데 어떻게 도움
이 될 수 있는지 보았습니다. 이 책 뒷부분에서 시퀀스 모델링에
RNN
을 사용해봅니다. [그
림
7
-
4
]와 [그림
7
-
5
]의 간단한
RNN
을 사용할 경우 언어에서 놓칠 수 있는 미묘한 특징(뉘
앙스 )이 있습니다. 앞서 언급한 피보나치 수열 예제처럼 다음 스텝으로 전달되는 문맥 정보
의 양은 스텝이 거듭될수록 감소합니다. 스텝
1
에서 뉴런의 출력은 스텝
2
에 큰 영향을 끼
치지만 스텝
3
에서는 영향이 작아지고 스텝
4
에서는 더 작아집니다. 따라서 ‘
Today
has ...
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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.