March 2026
Intermediate
504 pages
11h 26m
Korean
Content preview from 파이토치로 배우는 LLM & AI
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298
1
부
모델 구축
값
타임 스텝
검증 실젯값
검증 예측값
그림
11-5
최적화된
CNN
의 시계열 예측과 실젯값
CNN
하이퍼파라미터를 더 튜닝하면 더 좋은 성능을 얻을 수 있을 것입니다.
합성곱 이외에도
LSTM
을 포함해
RNN
으로 자연어 처리를 다룬 장에서 살펴본 기술은 시퀀스
데이터를 다룰 때 유용할 수 있습니다. 태생적으로
RNN
은 문맥을 유지하도록 고안되었으며
이전 스텝의 값이 다음 스텝의 값에 영향을 미칠 수 있습니다. 다음으로
RNN
을 사용한 시퀀스
모델링을 알아보겠습니다. 다만 그전에 합성 데이터셋에서 실전 데이터셋으로 이동해 보겠습
니다. 이번에는 날씨 데이터를 사용해 봅니다.
11.2
NASA
날씨 데이터 사용하기
시계열 날씨 데이터에 대한 훌륭한 자료는
NASA
의 고다드 우주 연구소 (
GISS
)에서 공개한
표면 온도 분석
Surface
Temperature
analysis
(
https
://
oreil
.
ly
/
6IixP
) 자료입니다. 페이지 오른쪽
에 있는
Station
Data
(
https
://
oreil
.
ly
/
F9Hmw
) 링크를 클릭하면 데이터를 얻으려는 기상
관측소를 선택할 수 있습니다. 예를 들면 시애틀 터코마
Seattle
Tacoma
국제공항을 선택하면 [그림
11
-
6
]과 같은 페이지가 열립니다.
299
11
장
시퀀스 모델을 위한 합성곱 신경망과 ...
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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.