Mathematical Foundations Data Analysis by Phillips Jeff (29 results)
Language: English
Published by Springer, 2021
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Condition: Good. Has some wear and creases. Has a remainder mark. hardcover Used - Good 2021.
Language: English
Published by Springer, 2022
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Published by Springer, 2022
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Language: English
Published by Springer, 2022
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Language: English
Published by Springer, 2021
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Published by Springer, 2021
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Language: English
Published by Springer, 2021
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Condition: New. pp. 287.
Language: English
Published by Springer, 2021
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Language: English
Published by Springer, 2022
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Language: English
Published by Springer, 2021
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Condition: New. pp. 287.
Language: English
Published by Springer, 2021
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Published by Springer, 2022
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Language: English
Published by Springer 2022-03, 2022
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Language: English
Published by Springer, 2022
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Language: English
Published by Springer, 2021
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Language: English
Published by Springer, 2021
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Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This textbook, suitable for an early undergraduate up to a graduate course, provides an overview of many basic principles and techniques needed for modern data analysis. In particular, this book was designed and written as preparation for students plannin…g to take rigorous Machine Learning and Data Mining courses. It introduces key conceptual tools necessary for data analysis, including concentration of measure and PAC bounds, cross validation, gradient descent, and principal component analysis. It also surveys basic techniques in supervised (regression and classification) and unsupervised learning (dimensionality reduction and clustering) through an accessible, simplified presentation. Students are recommended to have some background in calculus, probability, and linear algebra. Some familiarity with programming and algorithms is useful to understand advanced topics on computational techniques.
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Published by Springer, 2022
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Taschenbuch. Condition: Neu. Mathematical Foundations for Data Analysis | Jeff M. Phillips | Taschenbuch | Springer Series in the Data Sciences | xvii | Englisch | 2022 | Springer | EAN 9783030623432 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[d…ot]com | Anbieter: preigu.
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Published by Springer; 1st ed. 2021 edition (31 Mar. 2022), 2022
- Softcover
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Paperback. Condition: New. 1st ed. 2021.
Language: English
Published by Springer, 2022
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Condition: new. Questo è un articolo print on demand.
Language: English
Published by Springer, 2021
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Language: English
Published by Springer International Publishing Mrz 2021, 2021
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This textbook, suitable for an early undergraduate up to a graduate course, provides an overview of many basic principles and techniques needed for modern data analysis. In particular, this book was designed and written as preparation for…students planning to take rigorous Machine Learning and Data Mining courses. It introduces key conceptual tools necessary for data analysis, including concentration of measure and PAC bounds, cross validation, gradient descent, and principal component analysis. It also surveys basic techniques in supervised (regression and classification) and unsupervised learning (dimensionality reduction and clustering) through an accessible, simplified presentation. Students are recommended to have some background in calculus, probability, and linear algebra. Some familiarity with programming and algorithms is useful to understand advanced topics on computational techniques. 308 pp. Englisch.
Language: English
Published by Springer, Springer Mär 2022, 2022
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This textbook, suitable for an early undergraduate up to a graduate course, provides an overview of many basic principles and techniques needed for modern data analysis. In particular, this book was designed and written as preparati…on for students planning to take rigorous Machine Learning and Data Mining courses. It introduces key conceptual tools necessary for data analysis, including concentration of measure and PAC bounds, cross validation, gradient descent, and principal component analysis. It also surveys basic techniques in supervised (regression and classification) and unsupervised learning (dimensionality reduction and clustering) through an accessible, simplified presentation. Students are recommended to have some background in calculus, probability, and linear algebra. Some familiarity with programming and algorithms is useful to understand advanced topics on computational techniques. 308 pp. Englisch.
Language: English
Published by Springer, 2022
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Condition: New. Print on Demand.
Language: English
Published by Springer, 2022
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Language: English
Published by Springer International Publishing, 2021
- Hardcover
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides accessible, simplified introduction to core mathematical language and conceptsIntegrates examples of key concepts through geometric illustrations and Python codingAddresses topics in locality sensitive .
Language: English
Published by Springer, Berlin|Springer International Publishing|Springer, 2022
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Kartoniert / Broschiert. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This textbook, suitable for an early undergraduate up to a graduate course, provides an overview of many basic principles and techniques needed for modern data analysis. In particular, this bo…ok was designed and written as preparation for students planni.
Language: English
Published by Springer, Springer Mär 2022, 2022
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This textbook, suitable for an early undergraduate up to a graduate course, provides an overview of many basic principles and techniques needed for modern data analysis. In particular, this book was designed and written as preparation f…or students planning to take rigorous Machine Learning and Data Mining courses. It introduces key conceptual tools necessary for data analysis, including concentration of measure and PAC bounds, cross validation, gradient descent, and principal component analysis. It also surveys basic techniques in supervised (regression and classification) and unsupervised learning (dimensionality reduction and clustering) through an accessible, simplified presentation. Students are recommended to have some background in calculus, probability, and linear algebra. Some familiarity with programming and algorithms is useful to understand advanced topics on computational techniques.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 308 pp. Englisch.
Language: English
Published by Springer, Springer Mär 2021, 2021
- Hardcover
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Buch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This textbook, suitable for an early undergraduate up to a graduate course, provides an overview of many basic principles and techniques needed for modern data analysis. In particular, this book was designed and written as preparation for stud…ents planning to take rigorous Machine Learning and Data Mining courses. It introduces key conceptual tools necessary for data analysis, including concentration of measure and PAC bounds, cross validation, gradient descent, and principal component analysis. It also surveys basic techniques in supervised (regression and classification) and unsupervised learning (dimensionality reduction and clustering) through an accessible, simplified presentation. Students are recommended to have some background in calculus, probability, and linear algebra. Some familiarity with programming and algorithms is useful to understand advanced topics on computational techniques.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 308 pp. Englisch.
Language: English
Published by Palgrave Macmillan, 2022
- Softcover
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This textbook, suitable for an early undergraduate up to a graduate course, provides an overview of many basic principles and techniques needed for modern data analysis. In particular, this book was designed and written as preparation fo…r students planning to take rigorous Machine Learning and Data Mining courses. It introduces key conceptual tools necessary for data analysis, including concentration of measure and PAC bounds, cross validation, gradient descent, and principal component analysis. It also surveys basic techniques in supervised (regression and classification) and unsupervised learning (dimensionality reduction and clustering) through an accessible, simplified presentation. Students are recommended to have some background in calculus, probability, and linear algebra. Some familiarity with programming and algorithms is useful to understand advanced topics on computational techniques.
