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핸즈온 머신러닝: 사이킷런과 텐서플로를 활용한 머신러닝, 딥러닝 실무
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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
560
2
신경망과 딥러닝
for episode in range
(
500
):
episode
_
rewards
=
0
obs
=
env
.
reset
()
for step in range
(
1000
):
#
영원히
실행되면
곤란하므로
최대
스텝을
1000
번으로
합니다
.
action
=
basic
_
policy
(
obs
)
obs
,
reward
,
done
,
info
=
env
.
step
(
action
)
episode
_
rewards
+
=
reward
if done
:
break
totals
.
append
(
episode
_
rewards
)
이 코드는 쉽게 이해할 수 있을 것입니다. 결과를 확인해보겠습니다.
>>>
import numpy as np
>>>
np
.
mean
(
totals
),
np
.
std
(
totals
),
np
.
min
(
totals
),
np
.
max
(
totals
)
(
42
.
125999999999998
,
9
.
1237121830974033
,
24
.
0
,
68
.
0
)
500
번을 시도해도 이 정책은 막대를 쓰러뜨리지 않고
68
번보다 많은 스텝을 진행하지 못했습니
다. 그리 썩 좋지 않네요. 주피터 노트북 (
https
://
github
.
com
/
rickiepark
/
handson
-
ml
/
)
있는 시뮬레이션을 보면 카트가 시간이 갈수록 점점 더 크게 왼쪽과 오른쪽으로 진동해서 막대
가 너무 심하게 기울어지는 것을 ...
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박해선, 오렐리앙 제롱

Publisher Resources

ISBN: 9791162240731