May 2018
Beginner to intermediate
672 pages
16h 54m
Korean
Content preview from 핸즈온 머신러닝: 사이킷런과 텐서플로를 활용한 머신러닝, 딥러닝 실무
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123
3
장
분류
1
장에서는 가장 일반적인 지도 학습 작업이 회귀(값 예측 )와 분류 (클래스 예측 )라고 했습니
다.
2
장에서는 주택 가격을 예측하는 회귀 작업을 살펴보면서 선형 회귀, 결정 트리, 랜덤 포레
스트 (
7
장에서 더 자세히 설명합니다 ) 같은 여러 알고리즘을 보았습니다. 이 장에서는 분류 시
스템을 집중적으로 다루겠습니다.
3.1
MNIST
이 장에서는 고등학생과 미국 인구조사국 직원들이 손으로 쓴
70
,
000
개의 작은 숫자 이미지
를 모은
MNIST
데이터셋을 사용하겠습니다. 각 이미지에는 어떤 숫자를 나타내는지 레이블
되어 있습니다. 이 데이터셋은 학습용으로 아주 많이 사용되기 때문에 머신러닝 분야의 ‘
Hello
World
’라고 불립니다. 새로운 분류 알고리즘이 나올 때마다
MNIST
데이터셋에서 얼마나 잘
작동하는지 봅니다. 머신러닝을 배우는 사람이라면 머지않아
MNIST
데이터셋을 맞닥뜨리게
될 것입니다.
사이킷런에서 제공하는 여러 헬퍼 함수를 사용해 잘 알려진 데이터셋을 내려받을 수 있습니다.
MNIST
도 그중 하나입니다. 다음은
MNIST
데이터셋을 내려받는 코드입니다.
1
1
기본적으로 사이킷런은 내려받은 데이터셋을 $
HOME
/
scikit
_
learn
_
data
디렉터리에 캐싱합니다.
분류
CHAPTER
3
124
1
부
머신러닝
>>>
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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.