March 2026
Intermediate
504 pages
11h 26m
Korean
Content preview from 파이토치로 배우는 LLM & AI
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220
1
부
모델 구축
에폭
훈련 손실
검증 손실
손실
그림
7-20
드롭아웃을 적용한 스태킹
LSTM
의 손실
6
장에서 다루었던 데이터 전처리 방법은 물론 과대적합을 피하는 기술은 살펴볼 가치가 있습
니다. 하지만 아직 시도하지 않은 것이 하나 있습니다. 직접 임베딩을 훈련하는 대신, 사전에
학습된 임베딩을 사용하는 전이 학습입니다. 다음 절에서 자세히 알아보겠습니다.
7.4
RNN
에 사전 훈련된 임베딩 사용하기
앞선 예제에서는 훈련 세트에 있는 전체 단어로 어휘 사전을 만든 다음 이에 대한 임베딩을 훈
련했습니다. 처음에는 밀집 층에 전달하기 전에 하나의 벡터로 단어를 모았습니다. 이 장에서
는
RNN
을 사용해 성능을 향상하는 방법을 살펴보았습니다. 하지만 데이터셋에 있는 단어로만
제한되며 데이터셋에 있는 레이블을 사용해 임베딩을 훈련해야 합니다.
전이 학습을 소개했던
4
장을 다시 떠올려보죠. 임베딩을 직접 훈련하지 않고 사전 훈련된 임베
딩을 사용하면 어떨까요? 이 임베딩은 연구원들이 어려운 작업을 통해 단어를 벡터로 바꾸고
결과 벡터를 검증한 결과입니다. 사전 훈련된 임베딩의 한 가지 예는
6
장에서 본 스탠퍼드 대
학의 제프리 페닝턴
Jeffrey
Pennington
, 리처드 소셔
Richard
Socher
, 크리스토퍼 매닝
Christopher
Manning
이 ...
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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.