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fastai와 파이토치가 만나 꽃피운 딥러닝
book

fastai와 파이토치가 만나 꽃피운 딥러닝

by 박찬성, 김지은, 제러미 하워드, 실뱅 거거
August 2021
Beginner to intermediate
720 pages
15h 32m
Korean
Hanbit Media, Inc.
Content preview from fastai와 파이토치가 만나 꽃피운 딥러닝
542
3
딥러닝의 기반 지식
이제 이런
CNN
을 학습시키는 방법을 살펴보고,
fastai
가 학습을 효율적으로 하도록 내부적으
로 적용한 모든 기술을 보여 드리겠습니다.
13.4

7
3
을 잘 인식하는 모델은 이미 만들었으니, 이번에는 숫자
10
개를 모두 인식하는 좀 더 어
려운 문제에 도전하겠습니다.
MNIST
_
SAMPLE
대신
MNIST
를 사용하면 숫자
10
개를 포함한 데
이터셋을 얻을 수 있습니다.
>>> path = untar_data(URLs.MNIST)
>>> path.ls()
(#2) [Path(‘testing’),Path(‘training’)]
데이터는
training
testing
폴더에 나눠 저장됐습니다. 따라서
GrandparentSplitter
사용 시 그 사실을 알려줘야 합니다 (디폴트로는
train
valid
폴더를 찾죠 ). 그리고 차후
배치 크기를 손쉽게 변경하면서
DataLoaders
를 만드는
get
_
dls
함수를 정의합니다.
def get_dls(bs=64):
return DataBlock(
blocks=(ImageBlock(cls=PILImageBW), CategoryBlock),
get_items=get_image_files,
splitter=GrandparentSplitter(‘training’
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ISBN: 9791162244630