August 2021
Beginner to intermediate
720 pages
15h 32m
Korean
Content preview from fastai와 파이토치가 만나 꽃피운 딥러닝
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184
2
fastai 애플리케이션 계층 이해하기
4.1
영상 처리 모델에서 일어나는 일을 이해하려면 컴퓨터가 이미지를 다루는 방식을 먼저 이해해
야 합니다. 그러려면 이미지를 살펴볼 때 사용할 데이터가 필요한데, 여기서는 영상 처리 분야
에서 가장 유명한
MNIST
(
https
://
oreil
.
ly
/
g3RDg
) 데이터셋을 사용하겠습니다. 손으로
쓴 숫자 이미지로 구성된
MNIST
는 미국 국립표준기술원
National
Institute
of
Standards
and
Technology
에
서 수집했고, 얀 르쿤
Yann
Lecun
과 동료들이 머신러닝용 데이터셋으로 교정했습니다.
1998
년,
얀 르쿤은 손으로 쓴 숫자를 잘 인식하여 실제로도 널리 활용되는
LeNet
-
5
(
https
://
oreil
.
ly
/
LCNEx
) 시스템을 구축했습니다. 이때 활용한 데이터셋이 바로
MNIST
입니다. 이는
AI
역
사상 손꼽히는 중요한 발전입니다.
집념 그리고 딥러닝
딥러닝의 역사는 헌신적인 소수의 일부 연구자의 끈기와 집념이 이끌어왔습니다. 신경망은 초기
에 높은 관심을 받았지만
1990
년대와
2000
년대에는 소외당했습니다. 이때 소수의 연구자만이
신경망을 잘 작동하도록 만드는 데 지속적인 노력을 쏟아부었습니다. 그동안 머신러닝과 통계학
커뮤니티는
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and much more.
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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.