Dēta saiensu no tame no tōkeigaku nyūmon : yosoku, bunrui, tōkei moderingu, tōkeiteki kikai gakushū to R/Python puroguramingu /
データサイエンスのための統計学入門 : 予測, 分類, 統計モデリング, 統計的機械学習とR/Pythonプログラミング /
"Statistical methods are a key part of data science, yet few data scientists have formal statistical training. Courses and books on basic statistics rarely cover the topic from a data science perspective. The second edition of this practical guide-now including examples in Python as well as R-e...
Clasificación: | Libro Electrónico |
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Autores principales: | , , |
Otros Autores: | , |
Formato: | Electrónico eBook |
Idioma: | Japonés Inglés |
Publicado: |
Tōkyō-to Shinjuku-ku :
Orairī Japan,
2020.
|
Edición: | Dai 2-han. |
Temas: | |
Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
LEADER | 00000cam a22000007i 4500 | ||
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001 | OR_on1311518442 | ||
003 | OCoLC | ||
005 | 20231017213018.0 | ||
006 | m o d | ||
007 | cr cnu|||unuuu | ||
008 | 220420s2020 ja ob 001 0 jpn d | ||
040 | |a ORMDA |b eng |e rda |e pn |c ORMDA |d OCLCO |d OCLCF |d UAB |d STF |d UPM |d OCLCQ |d OCL | ||
066 | |c $1 |c Hani | ||
020 | |a 9784873119267 |q (electronic bk.) | ||
020 | |a 487311926X |q (electronic bk.) | ||
029 | 1 | |a AU@ |b 000071968829 | |
035 | |a (OCoLC)1311518442 | ||
037 | |a 9784873119267 |b O'Reilly Media | ||
041 | 1 | |a jpn |h eng | |
050 | 4 | |a QA276.4 | |
082 | 0 | 4 | |a 001.4/22 |2 23/eng/20220420 |
049 | |a UAMI | ||
100 | 1 | |a Bruce, Peter C., |d 1953- |e author. | |
240 | 1 | 0 | |a Practical statistics for data scientists. |l Japanese |
245 | 1 | 0 | |6 880-01 |a Dēta saiensu no tame no tōkeigaku nyūmon : |b yosoku, bunrui, tōkei moderingu, tōkeiteki kikai gakushū to R/Python puroguramingu / |c Peter Bruce, Andrew Bruce, Peter Gedeck cho ; Kurokawa Toshiaki ; Ōhashi Shin'ya gijutsu kanshū = Practical statistics for data scientists : 50+ essential concepts using R and Python / Peter Bruce, Andrew Bruce, and Peter Gedeck. |
246 | 3 | 1 | |a Practical statistics for data scientists : |b 50+ essential concepts using R and Python |
250 | |6 880-02 |a Dai 2-han. | ||
264 | 1 | |6 880-03 |a Tōkyō-to Shinjuku-ku : |b Orairī Japan, |c 2020. | |
300 | |a 1 online resource (396 pages) | ||
336 | |a text |b txt |2 rdacontent | ||
337 | |a computer |b c |2 rdamedia | ||
338 | |a online resource |b cr |2 rdacarrier | ||
588 | 0 | |a Online resource; title from title details screen (O'Reilly, viewed April 20, 2022). | |
504 | |a Includes bibliographical references (pages 345-349) and index. | ||
520 | |a "Statistical methods are a key part of data science, yet few data scientists have formal statistical training. Courses and books on basic statistics rarely cover the topic from a data science perspective. The second edition of this practical guide-now including examples in Python as well as R-explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not. Many data scientists use statistical methods but lack a deeper statistical perspective. If you're familiar with the R or Python programming languages, and have had some exposure to statistics but want to learn more, this quick reference bridges the gap in an accessible, readable format. With this updated edition, you'll dive into: Exploratory data analysis Data and sampling distributions Statistical experiments and significance testing Regression and prediction Classification Statistical machine learning Unsupervised learning." -- |c Provided by publisher. | ||
590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
650 | 0 | |a Mathematical analysis |x Statistical methods. | |
650 | 0 | |a Quantitative research |x Statistical methods. | |
650 | 0 | |a R (Computer program language) | |
650 | 0 | |a Python (Computer program language) | |
650 | 0 | |a Statistics |x Data processing. | |
650 | 6 | |a Analyse mathématique |x Méthodes statistiques. | |
650 | 6 | |a Recherche quantitative |x Méthodes statistiques. | |
650 | 6 | |a R (Langage de programmation) | |
650 | 6 | |a Python (Langage de programmation) | |
650 | 6 | |a Statistique |x Informatique. | |
650 | 7 | |a Quantitative research |x Statistical methods. |2 fast |0 (OCoLC)fst02013372 | |
650 | 7 | |a Mathematical analysis |x Statistical methods. |2 fast |0 (OCoLC)fst02013371 | |
650 | 7 | |a Python (Computer program language) |2 fast |0 (OCoLC)fst01084736 | |
650 | 7 | |a R (Computer program language) |2 fast |0 (OCoLC)fst01086207 | |
650 | 7 | |a Statistics |x Data processing. |2 fast |0 (OCoLC)fst01132113 | |
700 | 1 | |a Bruce, Andrew, |d 1958- |e author. | |
700 | 1 | |a Gedeck, Peter, |e author. | |
700 | 1 | |6 880-04 |a Kurokawa, Toshiaki, |e translator. | |
700 | 1 | |6 880-05 |a Ōhashi, Shin'ya. | |
765 | 0 | 8 | |i Translation of: |a Bruce, Peter C., 1953- |t Practical statistics for data scientists. |b Second edition. |d Sebastopol, CA : O'Reilly Media, Inc., 2020 |z 9781492072942 |w (DLC) 2018420845 |w (OCoLC)1158315601 |
856 | 4 | 0 | |u https://learning.oreilly.com/library/view/~/9784873119267/?ar |z Texto completo (Requiere registro previo con correo institucional) |
880 | 1 | 0 | |6 245-01/$1 |a データサイエンスのための統計学入門 : |b 予測, 分類, 統計モデリング, 統計的機械学習とR/Pythonプログラミング / |c Peter Bruce, Andrew Bruce, Peter Gedeck著 ; 黒川利明訳 ; 大橋真也技術監修 = Practical statistics for data scientists : 50+ essential concepts using R and Python / Peter Bruce, Andrew Bruce, and Peter Gedeck. |
880 | |6 250-02/$1 |a 第 2版. | ||
880 | 1 | |6 264-03/$1 |a 東京都新宿区 : |b オライリー・ジャパン, |c 2020. | |
880 | |6 520-00/$1 |a "データサイエンスにおいて重要な統計学と機械学習に関する52の基本概念と関連用語について、簡潔な説明とその知識の背景となる最低限の数式、グラフ、RとPythonのコードを提示し、多面的なアプローチにより、深い理解を促します。データの分類、分析、モデル化、予測という一連のデータサイエンスのプロセスにおいて統計学の必要な項目と不必要な項目を明確にし、統計学の基本と実践的なデータサイエンス技法を効率よく学ぶことができます。データサイエンス分野における昨今のPython人気を反映し、第1版ではRのみの対応だったコードが、今回の改訂でPythonにも対応。コードはすべてGitHubからダウンロード可能です。" -- |c Provided by publisher. | ||
880 | 1 | |6 700-04/$1 |a 黒川利明, |e translator. | |
880 | 1 | |6 700-05/$1 |a 大橋真也. | |
994 | |a 92 |b IZTAP |