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100%: Hamid R. Arabnia; Kevin Daimi; Robert Stahlbock; Cristina Soviany; Leonard Heilig; Kai Brüssau: Principles of Data Science (ISBN: 9783030439811) Springer Shop, in Englisch, auch als eBook.Nur diese Ausgabe anzeigen…
100%: Hamid R. Arabnia; Kevin Daimi; Robert Stahlbock; Cristina Soviany; Leonard Heilig; Kai Brüssau: Principles of Data Science (ISBN: 9783030439804) Springer Shop, in Englisch, Broschiert.Nur diese Ausgabe anzeigen…
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Bester Preis: Fr. 5.11 (€ 5.23)¹ (vom 01.04.2020)1
Principles of Data Science
~EN HC NWISBN: 9783030439804 bzw. 3030439801, vermutlich in Englisch, Springer Shop, gebundenes Buch, neu.
Lieferung aus: Mexiko, Lagernd, zzgl. Versandkosten.
This book provides readers with a thorough understanding of various research areas within the field of data science. The book introduces readers to various techniques for data acquisition, extraction, and cleaning, data summarizing and modeling, data analysis and communication techniques, data science tools, deep learning, and various data science applications. Researchers can extract and conclude various future ideas and topics that could result in potential publications or thesis. Furthermore, this book contributes to Data Scientists’ preparation and to enhancing their knowledge of the field. The book provides a rich collection of manuscripts in highly regarded data science topics, edited by professors with long experience in the field of data science. Introduces various techniques, methods, and algorithms adopted by Data Science experts Provides a detailed explanation of data science perceptions, reinforced by practical examples Presents a road map of future trends suitable for innovative data science research and practice, Hard cover.
This book provides readers with a thorough understanding of various research areas within the field of data science. The book introduces readers to various techniques for data acquisition, extraction, and cleaning, data summarizing and modeling, data analysis and communication techniques, data science tools, deep learning, and various data science applications. Researchers can extract and conclude various future ideas and topics that could result in potential publications or thesis. Furthermore, this book contributes to Data Scientists’ preparation and to enhancing their knowledge of the field. The book provides a rich collection of manuscripts in highly regarded data science topics, edited by professors with long experience in the field of data science. Introduces various techniques, methods, and algorithms adopted by Data Science experts Provides a detailed explanation of data science perceptions, reinforced by practical examples Presents a road map of future trends suitable for innovative data science research and practice, Hard cover.
2
Principles of Data Science
~EN NW EB DLISBN: 9783030439811 bzw. 303043981X, vermutlich in Englisch, Springer Shop, neu, E-Book, elektronischer Download.
Lieferung aus: Japan, Lagernd, zzgl. Versandkosten.
This book provides readers with a thorough understanding of various research areas within the field of data science. The book introduces readers to various techniques for data acquisition, extraction, and cleaning, data summarizing and modeling, data analysis and communication techniques, data science tools, deep learning, and various data science applications. Researchers can extract and conclude various future ideas and topics that could result in potential publications or thesis. Furthermore, this book contributes to Data Scientists’ preparation and to enhancing their knowledge of the field. The book provides a rich collection of manuscripts in highly regarded data science topics, edited by professors with long experience in the field of data science. Introduces various techniques, methods, and algorithms adopted by Data Science experts Provides a detailed explanation of data science perceptions, reinforced by practical examples Presents a road map of future trends suitable for innovative data science research and practice, eBook.
This book provides readers with a thorough understanding of various research areas within the field of data science. The book introduces readers to various techniques for data acquisition, extraction, and cleaning, data summarizing and modeling, data analysis and communication techniques, data science tools, deep learning, and various data science applications. Researchers can extract and conclude various future ideas and topics that could result in potential publications or thesis. Furthermore, this book contributes to Data Scientists’ preparation and to enhancing their knowledge of the field. The book provides a rich collection of manuscripts in highly regarded data science topics, edited by professors with long experience in the field of data science. Introduces various techniques, methods, and algorithms adopted by Data Science experts Provides a detailed explanation of data science perceptions, reinforced by practical examples Presents a road map of future trends suitable for innovative data science research and practice, eBook.
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