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핸즈온 머신러닝: 사이킷런과 텐서플로를 활용한 머신러닝, 딥러닝 실무
book

핸즈온 머신러닝: 사이킷런과 텐서플로를 활용한 머신러닝, 딥러닝 실무

by 박해선, 오렐리앙 제롱
May 2018
Beginner to intermediate
672 pages
16h 54m
Korean
Hanbit Media, Inc.
Content preview from 핸즈온 머신러닝: 사이킷런과 텐서플로를 활용한 머신러닝, 딥러닝 실무
392
2
신경망과 딥러닝
텐서플로를 사용해 드롭아웃을 구현하려면 간단하게
tf
.
layers
.
dropout
( )
함수를 입력층이
나 원하는 은닉층의 출력에 적용합니다. 훈련하는 동안 이 함수는 무작위로 뉴런을 제거하며
(출력을
0
으로 만듭니다) 나머지 출력을 보존 확률로 나눕니다.
57
훈련이 끝나면 이 함수는 전
혀 필요가 없습니다. 다음 코드는 세 개의 층으로 된 신경망에 드롭아웃 규제를 적용합니다.
58
[...]
training
=
tf
.
placeholder
_
with
_
default
(
False
,
shape
=
(),
name
=
'
training
')
dropout
_
rate
=
0
.
5
#
==
1
-
keep
_
prob
X
_
drop
=
tf
.
layers
.
dropout
(
X
,
dropout
_
rate
,
training
=
training
)
with tf
.
name
_
scope
("
dnn
"):
hidden1
=
tf
.
layers
.
dense
(
X
_
drop
,
n
_
hidden1
,
activation
=
tf
.
nn
.
relu
,
name
=
"
hidden1
")
hidden1
_
drop
=
tf
.
layers
.
dropout
(
hidden1
,
dropout
_
rate
,
training
=
training
)
hidden2
=
tf
.
layers
.
dense
(
hidden1
_
drop
,
n
_
hidden2
,
activation
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박해선, 오렐리앙 제롱

Publisher Resources

ISBN: 9791162240731