December 2021
Beginner to intermediate
468 pages
11h 42m
Korean
Content preview from 금융 전략을 위한 머신러닝: 19가지 사례를 통해 익히는 금융 전략, 머신러닝, 데이터 과학
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32
1
부
프레임워크
많은 개발자가 파이썬의 단순성에 끌려 머신러닝을 위한 새로운 라이브러리를 만들고 파이썬
채택을 손쉽게 결정한다.
2.2
머신러닝을 위한 파이썬 패키지
[그림
2
-
1
]은 머신러닝에서 주로 사용하는 파이썬 패키지를 보여 준다.
NumPy Pandas
Keras
Theano TensorFlow
Seaborn
Conda
SciPy
Scikit-learn
StatsModels
Matplotlib
pip
데이터 표현
머신러닝, 통계 분석
데이터 시각화
패키지 관리
그림
2-1
파이썬 패키지
아래에 각 패키지를 간략히 요약했다.
●
넘파이
NumPy
방대한 수식 함수와 다차원 배열을 지원한다.
●
판다스
Pandas
데이터 처리 및 분석을 위한 라이브러리. 다른 기능이 여럿 있지만 테이블형 데이터 구조를 처리하고 변
형하는 기능을 제공한다.
●
맷플롯립
Matplotlib
2
차원 차트와 그래프를 생성하는 라이브러리이다.
●
사이파이
SciPy
넘파이, 판다스, 맷플롯립을 결합한 것으로 수학, 과학, 공학을 위한 파이썬 라이브러리 생태계이다.
33
2
장
머신러닝 모델 개발
●
사이킷런 ...
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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.
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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.