January 2017
Beginner to intermediate
312 pages
7h 3m
Korean
Content preview from 밑바닥부터 시작하는 딥러닝
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125
4
장
-
신경망 학습
>>>
numerical
_
diff
(
function
_
1
,
5
)
0
.
1999999999990898
>>>
numerical
_
diff
(
function
_
1
,
10
)
0
.
2999999999986347
이렇게 계산한 미분 값이
x
에 대한
f
(
x
)의 변화량입니다. 즉, 함수의 기울기에 해당합니다. 또
한
f
(
x
) =
0
.
01
x
2
+
0
.
1
x
의 해석적 해법은
dx
df x
x
()
..
00
20
1
=+
입니다. 그래서
x
가
5
와
10
일 때
의 ‘진정한 미분’은 차례로
0
.
2
와
0
.
3
이 됩니다. 앞의 수치 미분과 결과를 비교하면 그 오차가
매우 작음을 알 수 있습니다. 실제로 거의 같은 값이라고 해도 될 만큼 작은 오차입니다.
이제 앞에서 구한 수치 미분 값을 기울기로 하는 직선을 그려보겠습니다. 결과는 [그림
4
-
7
]
과 같이 되어, 함수의 접선에 해당하는 것을 확인할 수 있습니다(
ch04
/
gradient
_
1d
.
py
).
그림
4-7
x
=
5
,
x
=
10
에서의 접선 : 직선의 기울기는 수치 미분에서 구한 값을 사용하였다.
4.3.3
편미분
이어서 [식
4
.
6
]과 같은 함수를 살펴보시죠. 인수들의 제곱 합을 계산하는 단순한 식입니다만,
앞의 예와 달리 변수가
2
개라는 점에 주의해야 합니다.
f
(
x
0
,
x
1
) =
x
0
2
+
x
1
2
[식 4.6 ]
이 식은 파이썬으로 ...
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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.