March 2026
Intermediate
504 pages
11h 26m
Korean
Content preview from 파이토치로 배우는 LLM & AI
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75
2
장
컴퓨터 비전 소개
배치 400, 손실: 0.309722, 정확도: 88.67% [25600/60000]
배치 500, 손실: 0.310240, 정확도: 88.60% [32000/60000]
배치 600, 손실: 0.306988, 정확도: 88.70% [38400/60000]
배치 700, 손실: 0.308556, 정확도: 88.64% [44800/60000]
배치 800, 손실: 0.309518, 정확도: 88.67% [51200/60000]
배치 900, 손실: 0.311487, 정확도: 88.59% [57600/60000]
완료!
이제 테스트 데이터의 정확도 (
86
.
9
%)가 훈련 데이터의 정확도(
88
.
59
%)보다 낮은 이유가 궁
금할 것입니다. 이는 매우 일반적인 현상으로 생각해 보면 당연한 결과입니다. 신경망은 훈련
에 사용한 입력을 출력에 매칭하는 방법을 알 뿐입니다. 충분히 많은 데이터를 제공하면 신경
망이 훈련 과정에서 보았던 샘플을 일반화하여 신발이나 드레스가 어떤 모습인지 학습하기를
희망합니다. 하지만 신경망이 본 적이 없고 혼란을 주기에 충분한 샘플은 항상 존재합니다.
예를 들어 여러분이 스니커즈만 보고 자랐다면 스니커즈가 신발의 전부라고 생각할 것이며, 만
약 하이힐을 처음 보게 되면 당황할 수 있습니다. 여러분의 경험에 따라 ...
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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.
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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.