March 2018
Beginner to intermediate
332 pages
6h 1m
Korean
Content preview from 9가지 사례로 익히는 고급 스파크 분석(2판): 현실 세계 빅데이터로 배우는 데이터 과학과 머신러닝
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102
9가지 사례로 익히는 고급 스파크 분석 (2판)
4.1
회귀로 돌아와서
통계학이 체계를 갖춘 지 한 세기 이상이 지나고 머신러닝과 데이터 과학이 등장한 오늘날에
도, 주어진 값들로부터 새로운 값을 예측하는 방법으로 ‘회귀 (
https
://
goo
.
gl
/
yFA7xy
)’를 꼽는
다. 심지어 값이 평균에 가까워지거나 실제로 가까워지려는 움직임조차 없을지라도 말이다. 또
한, 회귀 기법은 분류 기법과 연관이 있다(
https
://
goo
.
gl
/
Tq7xfG
). 일반적으로
회귀
는 크기,
수입, 온도와 같은 숫자를 예측하며,
분류
는 ‘스팸 메일’, ‘고양이 사진’과 같은 레이블이나 범주
를 예측하는 데 사용한다.
회귀와 분류는 모두 하나 이상의 값이 주어졌을 때 하나 이상의 값을 예측해낸다. 이를 위해서
학습을 위한 입출력 체계가 구성되어 있어야 하며, 질문과 이에 대한 답변도 제공되어야 한다.
이러한 탓에 회귀와 분류는
지도 학습
Supervised
Learning
(
https
://
goo
.
gl
/
ktFn24
) 유형에 들어간다.
분류와 회귀는 가장 오래되고 가장 잘 연구된 유형의 예측 분석이다. 서포트 벡터 머신
Support
Vector
Machine
, 로지스틱 회귀
Logistic
Regression
, 나이브 베이즈 분류
Naïve
Bayes
, 신경망
Neural
Network
, 딥러
닝
Deep
Learning
과 같은 분석 패키지나 라이브러리에서 자주 접하는 대부분의 알고리즘은 분류와
회귀 기법이다.
3
장의 주제인 추천 엔진도 더 직관적이라는 이유로
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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.