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Advanced data science and analytics with Python

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Advanced data science and analytics with Python/ Jesús Rogel-Salazar.
作者:	Rogel-Salazar, Jesús.
出版者:	Boca Raton, FL :CRC Press, : 2020.,
面頁冊數:	1 online resource :ill.
標題:	Data mining. -
電子資源:	https://www.taylorfrancis.com/books/9780429446641
ISBN:	9780429446641

Advanced data science and analytics with Python
Rogel-Salazar, Jesús.

Advanced data science and analytics with Python[electronic resource] /Jesús Rogel-Salazar. - 1st ed. - Boca Raton, FL :CRC Press,2020. - 1 online resource :ill. - Chapman & Hall/CRC data mining & knowledge discovery series. - Chapman & Hall/CRC data mining & knowledge discovery series..

Includes bibliographical references (p. [369]-378) and index.

"Advanced Data Science and Analytics with Python enables data scientists to continue developing their skills and apply them in business as well as academic settings. The subjects discussed in this book are complementary and a follow up from the topics discuss in Data Science and Analytics with Python. The aim is to cover important advanced areas in data science using tools developed in Python such as SciKit-learn, Pandas, Numpy, Beautiful Soup, NLTK, NetworkX and others. The model development is supported by the use of frameworks such as Keras, TensorFlow and Core ML, as well as Swift for the development of iOS and MacOS applications. The book can be read independently from the previous volume and each of the chapters in this volume is sufficiently independent from the others providing flexibility for the reader. Each of the topics addressed in the book tackles the data science workflow from a practical perspective, concentrating on the process and results obtained. The implementation and deployment of trained models are central to the book. Time series analysis, natural language processing, topic modelling, social network analysis, neural networks and deep learning are comprehensively covered in the book. The book discusses the need to develop data products and tackles the subject of bringing models to their intended audiences. In this case literally to the users's fingertips in the form of an iPhone app"--

ISBN: 9780429446641

LCCN: 2019055620Subjects--Topical Terms:

562972
Data mining.

LC Class. No.: QA76.9.D343 / R637 2020

Dewey Class. No.: 006.3/12

Advanced data science and analytics with Python
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490 1 $a Chapman & Hall/CRC data mining & knowledge discovery series
504 $a Includes bibliographical references (p. [369]-378) and index.
520 $a "Advanced Data Science and Analytics with Python enables data scientists to continue developing their skills and apply them in business as well as academic settings. The subjects discussed in this book are complementary and a follow up from the topics discuss in Data Science and Analytics with Python. The aim is to cover important advanced areas in data science using tools developed in Python such as SciKit-learn, Pandas, Numpy, Beautiful Soup, NLTK, NetworkX and others. The model development is supported by the use of frameworks such as Keras, TensorFlow and Core ML, as well as Swift for the development of iOS and MacOS applications. The book can be read independently from the previous volume and each of the chapters in this volume is sufficiently independent from the others providing flexibility for the reader. Each of the topics addressed in the book tackles the data science workflow from a practical perspective, concentrating on the process and results obtained. The implementation and deployment of trained models are central to the book. Time series analysis, natural language processing, topic modelling, social network analysis, neural networks and deep learning are comprehensively covered in the book. The book discusses the need to develop data products and tackles the subject of bringing models to their intended audiences. In this case literally to the users's fingertips in the form of an iPhone app"-- $c Provided by publisher.
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