May 2018
Beginner to intermediate
672 pages
16h 54m
Korean
Content preview from 핸즈온 머신러닝: 사이킷런과 텐서플로를 활용한 머신러닝, 딥러닝 실무
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503
14
장
순환 신경망
stacked
_
rnn
_
outputs
=
tf
.
reshape
(
rnn
_
outputs
,
[
-
1
,
n
_
neurons
])
stacked
_
outputs
=
tf
.
layers
.
dense
(
stacked
_
rnn
_
outputs
,
n
_
outputs
)
outputs
=
tf
.
reshape
(
stacked
_
outputs
,
[
-
1
,
n
_
steps
,
n
_
outputs
])
나머지 코드는 이전과 동일합니다. 이 코드는 타임 스텝마다 완전 연결 층을 만들지 않고 하나
의 완전 연결 층만 만들기 때문에 속도가 훨씬 빠릅니다.
14.3.3
RNN
의 창조성
지금까지 미래를 예측할 수 있는 모델을 만들었습니다. 이 모델을 사용해 이 장의 앞에서 언급
했던 새로운 시퀀스를 창조할 수 있습니다. 생성을 위해 필요한 것은
n
_
steps
값을 가지는 시
드
seed
시퀀스 (예를 들면
0
으로 채워진 시퀀스 )를 제공하는 것입니다. 그런 다음 예측한 값을
시퀀스 끝에 추가하고, 마지막
n
_
steps
값을 모델에 주입하여 다음 값을 예측하는 식입니다.
이 과정은 원본 시계열 데이터와 비슷한 새로운 시퀀스를 생성합니다(그림
14
-
11
).
sequence
=
[
0
.]
*
n
_
steps
for iteration in range
(
300
):
X
_
batch
=
np
.
array
(
sequence
[
-
n
_
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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.