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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448
파이썬 라이브러리를 활용한 머신러닝(번역개정판)
전체 데이터를 이용하여 학습한 모델의 테스트 점수는
87
.
5
%로, 분류 정확도가 꽤 높습니다.
여기에 사용된 주피터 노트북은 역자의 깃허브에
07
-
konlpy
.
ipynb
이름으로 업로드되어 있
습니다.
참고자료
•
http
://
konlpy
.
org
/
ko
/
•
https
://
www
.
lucypark
.
kr
/
slides
/
2015
-
pyconkr
/#
39
•
https
://
github
.
com
/
e9t
/
nsmc
/
7.9
토픽 모델링과 문서 군집화
텍스트 데이터에 자주 적용하는 특별한 기법으로
토픽 모델링
topic
modeling
이 있습니다. 이 용어
는 비지도 학습으로 문서를 하나 또는 그 이상의 토픽으로 할당하는 작업을 통칭합니다. ‘정치’,
‘스포츠’, ‘금융’ 등의 토픽으로 묶을 수 있는 뉴스 데이터가 좋은 예입니다. 한 문서가 하나의 토
픽에 할당되면 이는
3
장에서 본 것과 같은 문서를 군집시키는 문제가 됩니다. 문서가 둘 이상
의 토픽을 가질 수 있다면 이는
3
장에서 본 분해 방법과 관련이 있습니다. 학습된 각 성분은 하
나의 토픽에 해당하며 문서를 표현한 성분의 계수는 문서가 어떤 토픽에 얼마만큼 연관되어
있는지를 말해줍니다. 사람들이 토픽 모델링에 대해 이야기할 때 종종
잠재 디리클레 할당
Latent
Dirichlet ...
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and much more.
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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.