Data science in practice [electronic resource]

• 作者： Alby, Tom, author, translator.
• 其他題名：
  • Data Science in der Praxis.
• 出版： Boca Raton ;London : CRC Press, Taylor & Francis Group
• 叢書名： Chapman & Hall/CRC data science series
• 主題： Data mining. , Big data. , Quantitative research--Methodology. , R (Computer program language) , Exploration de donnees (Informatique) , Donnees volumineuses. , Recherche quantitative--Methodologie. , R (Langage de programmation) , MATHEMATICS / Probability & Statistics / General , Big data. , Data mining. , R (Computer program language)
• ISBN： 9781003426363 (electronic bk.) 、 1003426360 、 9781000955668 (electronic bk.) 、 1000955664 、 9781000955644 (electronic bk.) 、 1000955648 (electronic bk.)
• FIND@SFXID: CGU
• 資料類型: 電子書
• 內容註: "Copyright 2022 Rheinwerk Verlag GmbH. All rights reserved. First published inthe German language under the title "Data Science in der Praxis" (ISBN 978-3-8362-8462-2) by Rheinwerk Verlag GmbH, Bonn, Germany. Translated into English from German by Tom Alby." Includes bibliographical references and index. Machine learning, data science and artificial intelligence -- The anatomy of a data science project -- Introduction to R -- Exploratory data analysis -- Forecasting -- Clustering -- Classification -- Other use cases -- Workflows and tools -- Ethical handling of data and algorithms -- Next steps after this book?
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• 摘要註: "Data Science in Practice is the ideal introduction to data science. With or without math skills: Here you get the all-round view that you need for your projects. This book describes how to properly question data, in order to unearth the treasure that data can be. You will get to know the relevant analysis methods, and will be introduced to the programming language R, which is ideally suited for data analysis. Associated tools like notebooks that make data science programming easily accessible are included in this introduction. Because technology alone is not enough, this book also deals with problems in project implementation, illuminates various fields of application and does not forget to address ethical aspects. Data Science in Practice includes many examples, notes on errors, decision-making aids and other practical tips. This book is ideal as a complementary text for university students, and is a useful learning tool for those moving into more data-related roles"--
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