July 2018
Intermediate to advanced
596 pages
13h 35m
Japanese
Content preview from Pythonによるデータ分析入門 第2版 ―NumPy、pandasを使ったデータ処理
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1.3
必須の
Python
ライブラリ
7
scipy.integrate
数値積分ルーチンや微分方程式ソルバ（
solver
）
scipy.linalg
線形代数ルーチンや、
numpy.linalg
で提供されている機能を拡張した行列の分解機能
scipy.optimize
関数の最適化（最小化）と求根アルゴリズム
scipy.signal
信号処理ツール
scipy.sparse
疎（スパース）なデータを持つ行列や線形システムのソルバ
scipy.special
ガンマ関数のような多数の一般的な数学の関数を実装した
Fortran
のライブラリ
SPECFUN
を
使うためのラッパー
scipy.stats
標準的な連続分布や離散分布（密度関数、サンプラー、連続分布関数）、さまざまな統計検定、
その他の記述統計
NumPy
と
SciPy
を一緒に用いることで、それらを合理的で成熟した計算基盤として扱うことができ、
多くの伝統的な科学計算に
適用することができます。
1.3.6
scikit-learn
2010
年にプロジェクトが開始されて以来、
scikit-learn
（
http://scikit-learn.org
）は、
Python
プログラ
マにとって、一般的な機械学習ツールのトップに立つものになりました。たったの
7
年のうちに、世界
中の
1,500
人にもおよぶ貢献者を得ています。
scikit-learn
には、次のようなサブモジュールがあります。
●
分類：
SVM
や最近傍法、ランダムフォレスト、ロジスティック回帰など
●
回帰：
Lasso
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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.