April 2019
Beginner to intermediate
480 pages
12h 34m
Korean
Content preview from 파이썬 라이브러리를 활용한 머신러닝(번역개정판): 사이킷런 핵심 개발자가 쓴 머신러닝과 데이터 과학 실무서
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220
파이썬 라이브러리를 활용한 머신러닝(번역개정판)
면 독립 성분 분석 (
ICA
), 요인 분석 (
FA
), 희소 코딩
sparse
coding
(딕셔너리
dictionary
학습 )에 관
해 설명하고 있는
scikit
-
learn
사용자 가이드의 분해 메서드 페이지를 살펴보길 추천합니다
(
http
://
scikit
-
learn
.
org
/
stable
/
modules
/
decomposition
.
html
).
3.4.3
t
-
SNE
를 이용한 매니폴드 학습
데이터를 산점도로 시각화할 수 있다는 이점 때문에
PCA
가 종종 데이터 변환에 가장 먼저 시
도해볼 만한 방법이지만,
LFW
데이터셋의 산점도에서 본 것처럼 알고리즘의 (회전하고 방향
을 제거하는) 태생상 유용성이 떨어집니다.
매니폴드 학습
manifold
learning
알고리즘이라고 하는 시
각화 알고리즘들은 훨씬 복잡한 매핑을 만들어 더 나은 시각화를 제공합니다. 특별히
t
-
SNE
26
알고리즘을 아주 많이 사용합니다.
매니폴드 학습 알고리즘은 그 목적이 시각화라
3
개 이상의 특성을 뽑는 경우는 거의 없습니다.
t
-
SNE
를 포함해서 일부 매니폴드 알고리즘들은 훈련 데이터를 새로운 표현으로 변환시키지
만 새로운 데이터에는 적용하지 못합니다. 즉 테스트 세트에는 적용할 수 없고, 단지 훈련했던
데이터만 변환할 수 있습니다. 그래서 매니폴드 ...
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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.