大葉大學圖書館 |

Data science and analytics with Python[electronic resource] /

紀錄類型:	書目-電子資源 : Monograph/item
杜威分類號:	006.3/12
書名/作者:	Data science and analytics with Python/ Jesús Rogel-Salazar.
作者:	Rogel-Salazar, Jesús.
出版者:	Boca Raton, FL : : CRC Press,, c2017.
面頁冊數:	1 online resource (400 p.) : : ill.
附註:	"A Chapman & Hall book"--Title page.
標題:	Data mining.
標題:	Python (Computer program language)
標題:	Databases.
ISBN:	9781315151670
書目註:	Includes bibliographical references (p. 361-368) and index.
摘要、提要註:	Data Science and Analytics with Python is designed for practitioners in data science and data analytics in both academic and business environments. The aim is to present the reader with the main concepts used in data science using tools developed in Python, such as SciKit-learn, Pandas, Numpy, and others. The use of Python is of particular interest, given its recent popularity in the data science community. The book can be used by seasoned programmers and newcomers alike. The book is organized in a way that individual chapters are sufficiently independent from each other so that the reader is comfortable using the contents as a reference. The book discusses what data science and analytics are, from the point of view of the process and results obtained. Important features of Python are also covered, including a Python primer. The basic elements of machine learning, pattern recognition, and artificial intelligence that underpin the algorithms and implementations used in the rest of the book also appear in the first part of the book. Regression analysis using Python, clustering techniques, and classification algorithms are covered in the second part of the book. Hierarchical clustering, decision trees, and ensemble techniques are also explored, along with dimensionality reduction techniques and recommendation systems. The support vector machine algorithm and the Kernel trick are discussed in the last part of the book.
電子資源:	https://www.taylorfrancis.com/books/9781315151670

Data science and analytics with Python[electronic resource] /
Rogel-Salazar, Jesús.

Data science and analytics with Python[electronic resource] /Jesús Rogel-Salazar. - 1st ed. - Boca Raton, FL :CRC Press,c2017. - 1 online resource (400 p.) :ill. - Chapman & Hall/CRC data mining and knowledge discovery series. - Chapman & Hall/CRC data mining and knowledge discovery series..

"A Chapman & Hall book"--Title page.

Includes bibliographical references (p. 361-368) and index.

Data Science and Analytics with Python is designed for practitioners in data science and data analytics in both academic and business environments. The aim is to present the reader with the main concepts used in data science using tools developed in Python, such as SciKit-learn, Pandas, Numpy, and others. The use of Python is of particular interest, given its recent popularity in the data science community. The book can be used by seasoned programmers and newcomers alike. The book is organized in a way that individual chapters are sufficiently independent from each other so that the reader is comfortable using the contents as a reference. The book discusses what data science and analytics are, from the point of view of the process and results obtained. Important features of Python are also covered, including a Python primer. The basic elements of machine learning, pattern recognition, and artificial intelligence that underpin the algorithms and implementations used in the rest of the book also appear in the first part of the book. Regression analysis using Python, clustering techniques, and classification algorithms are covered in the second part of the book. Hierarchical clustering, decision trees, and ensemble techniques are also explored, along with dimensionality reduction techniques and recommendation systems. The support vector machine algorithm and the Kernel trick are discussed in the last part of the book.

ISBN: 9781315151670Subjects--Topical Terms:

337740
Data mining.

LC Class. No.: QA76.9 / .D343 2017

Dewey Class. No.: 006.3/12

Data science and analytics with Python[electronic resource] /
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300 $a 1 online resource (400 p.) : $b ill.
490 1 $a Chapman & Hall/CRC data mining and knowledge discovery series
500 $a "A Chapman & Hall book"--Title page.
504 $a Includes bibliographical references (p. 361-368) and index.
520 3 $a Data Science and Analytics with Python is designed for practitioners in data science and data analytics in both academic and business environments. The aim is to present the reader with the main concepts used in data science using tools developed in Python, such as SciKit-learn, Pandas, Numpy, and others. The use of Python is of particular interest, given its recent popularity in the data science community. The book can be used by seasoned programmers and newcomers alike. The book is organized in a way that individual chapters are sufficiently independent from each other so that the reader is comfortable using the contents as a reference. The book discusses what data science and analytics are, from the point of view of the process and results obtained. Important features of Python are also covered, including a Python primer. The basic elements of machine learning, pattern recognition, and artificial intelligence that underpin the algorithms and implementations used in the rest of the book also appear in the first part of the book. Regression analysis using Python, clustering techniques, and classification algorithms are covered in the second part of the book. Hierarchical clustering, decision trees, and ensemble techniques are also explored, along with dimensionality reduction techniques and recommendation systems. The support vector machine algorithm and the Kernel trick are discussed in the last part of the book.
588 $a Description based on print version record.
650 0 $a Data mining. $3 337740
650 0 $a Python (Computer program language) $3 339754
650 0 $a Databases. $3 381648
830 0 $a Chapman & Hall/CRC data mining and knowledge discovery series. $3 488186
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