March 2026
Intermediate
504 pages
11h 26m
Korean
Content preview from 파이토치로 배우는 LLM & AI
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85
3
장
고급 컴퓨터 비전: 이미지에서 특징 감지하기
는 픽셀이
16
에서
4
로
75
% 줄어듭니다. 각 풀링 과정에서 선택한 최댓값을 새로운 이미지로
만들기 때문입니다.
[그림
3
-
5
]는 [그림
3
-
2
]의 이미지에 수직 필터를 적용하고 최대 풀링을 적용한 모습입니다.
그림
3-5
수직 필터와 최대 풀링을 적용한 이미지
필터로 추출한 특성이 유지될 뿐만 아니라 강조되었습니다. 또한 이미지 크기가 원본 크기
512
×
512
에서
256
×
256
로
1
/
4
줄었습니다.
NOTE
_
이외에도 풀에서 가장 작은 값을 선택하는 최소 풀링
min
pooling
과 평균값을 선택하는 평균 풀링
average
pooling
이 있습니다.
3.3
합성곱 신경망 만들기
2
장에서 패션
MNIST
이미지를 인식하는 신경망을 만들었습니다. 해당 코드는 다음과 같습
니다.
# 모델 정의
class FashionMNISTModel(nn.Module):
def __init__(self):
super(FashionMNISTModel, self).__init__()
self.flatten = nn.Flatten()
self.linear_relu_stack = nn.Sequential(
86
1
부
모델 구축
nn.Linear(28*28, 128),
nn.ReLU(),
nn.Linear(128 ...
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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.