May 2020
Beginner to intermediate
952 pages
24h 11m
Korean
Content preview from 핸즈온 머신러닝(2판): 사이킷런, 케라스, 텐서플로 2를 활용한 머신러닝, 딥러닝 완벽 실무
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665
16
장
RNN과 어텐션을 사용한 자연어 처리
식
16-3
스케일드 점-곱 어텐션
AttentionsoftmaxQKV
QK
V,,
()
=
d
keys
이 식을 살펴봅시다.
•
Q
는 행마다 쿼리
query
하나를 담은 행렬입니다. 이 행렬의 크기는 [
n
queries
,
d
keys
]입니다. 여기에서
n
queries
는
쿼리 개수입니다.
d
keys
는 쿼리와 키의 차원 개수입니다.
•
K
는 행마다 키
key
하나를 담은 행렬입니다. 이 행렬의 크기는 [
n
keys
,
d
keys
]입니다. 여기에서
n
keys
는 키와 값
의 개수입니다.
•
V
는 행마다 값
value
하나를 담은 행렬입니다. 이 행렬의 크기는 [
n
keys
,
d
values
]입니다. 여기에서
d
values
는 값의
차원입니다.
•
QK
T
의 크기는 [
n
queries
,
n
keys
]입니다. 이 행렬은 쿼리/키 쌍마다 하나의 유사도 점수를 담고 있습니다. 소프
트맥스 함수의 출력도 동일한 크기이지만 모든 행은 합이
1
입니다. 최종 출력의 크기는 [
n
queries
,
d
values
]입니
다. 하나의 행은 하나의 쿼리에 해당합니다. 각 행은 쿼리 결과 (값의 가중치 합 )를 나타냅니다.
•
스케일링 인자는 소프트맥스 함수가 포화되어 그레이디언트가 너무 작아지지 않도록 유사도 점수를 낮춥
니다.
•
소프트맥스 함수를 계산하기 전에 ...
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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.