August 2021
Beginner to intermediate
720 pages
15h 32m
Korean
Content preview from fastai와 파이토치가 만나 꽃피운 딥러닝
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64
1
실전 딥러닝
이미지 인식 모델을 학습시키는 다섯 번째 줄의 코드는
convolutional
neural
network
(
CNN
)을 생성합니다. 이때 학습에 사용할 데이터셋과 모델의
(모델의 종류 )
및
metric
를 지정합니다.
learn = cnn_learner(dls, resnet34, metrics=error_rate)
왜
CNN
을 사용했을까요?
CNN
은 영상 처리 모델을 만드는 최신 접근법이기 때문입니다. 이
책에서
CNN
의 작동 방식을 모두 배우겠지만, 당장은 사람의 시각 시스템이 작동하는 방식에
서 영감을 받은 신경망 구조라는 점만 알아두세요.
fastai
는 여러 가지 모델을 제공하며, 앞으로 차차 알아보겠습니다(물론 여러분만의 구조를 만
드는 방법도 다룹니다). 그러나 일반적으로 모델의 구조를 선택하는 일은 딥러닝의 전체 과정
에서 크게 중요한 부분이 아닙니다. 학계에서는 모델의 구조를 다루기를 좋아하지만, 실제로는
여기에 많은 시간을 할애할 필요는 없습니다. 대부분의 상황에서 잘 작동하는 몇 가지 표준 구
조가 있기 때문이죠. 여기서는 앞으로 많이 다룰
이라는 구조의 모델을 사용합니다. 여
러 데이터셋과 문제에서 빠르고 정확하게 작동하는 모델이죠.
resnet34
에서
34
는 이 구조에
있는
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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.