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Langue: anglais
Edité par O'Reilly Media, Incorporated, 2017
ISBN 10 : 1491934115 ISBN 13 : 9781491934111
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Ajouter au panierPaperback. Etat : New. Data Science is booming thanks to R and Python, but Java brings the robustness, convenience, and ability to scale critical to today's data science applications. With this practical book, Java software engineers looking to add data science skills will take a logical journey through the data science pipeline. Author Michael Brzustowicz explains the basic math theory behind each step of the data science process, as well as how to apply these concepts with Java.You'll learn the critical roles that data IO, linear algebra, statistics, data operations, learning and prediction, and Hadoop MapReduce play in the process. Throughout this book, you'll find code examples you can use in your applications.Examine methods for obtaining, cleaning, and arranging data into its purest formUnderstand the matrix structure that your data should takeLearn basic concepts for testing the origin and validity of dataTransform your data into stable and usable numerical valuesUnderstand supervised and unsupervised learning algorithms, and methods for evaluating their successGet up and running with MapReduce, using customized components suitable for data science algorithms.
Langue: anglais
Edité par O'Reilly Media 6/22/2017, 2017
ISBN 10 : 1491934115 ISBN 13 : 9781491934111
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Ajouter au panierPaperback or Softback. Etat : New. Data Science with Java: Practical Methods for Scientists and Engineers. Book.
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Ajouter au panierPaperback. Etat : New. Data Science is booming thanks to R and Python, but Java brings the robustness, convenience, and ability to scale critical to today's data science applications. With this practical book, Java software engineers looking to add data science skills will take a logical journey through the data science pipeline. Author Michael Brzustowicz explains the basic math theory behind each step of the data science process, as well as how to apply these concepts with Java.You'll learn the critical roles that data IO, linear algebra, statistics, data operations, learning and prediction, and Hadoop MapReduce play in the process. Throughout this book, you'll find code examples you can use in your applications.Examine methods for obtaining, cleaning, and arranging data into its purest formUnderstand the matrix structure that your data should takeLearn basic concepts for testing the origin and validity of dataTransform your data into stable and usable numerical valuesUnderstand supervised and unsupervised learning algorithms, and methods for evaluating their successGet up and running with MapReduce, using customized components suitable for data science algorithms.
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Langue: anglais
Edité par O'Reilly Media 2016-04-25, 2016
ISBN 10 : 1491934115 ISBN 13 : 9781491934111
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Langue: anglais
Edité par O'Reilly Media, Inc, USA, 2017
ISBN 10 : 1491934115 ISBN 13 : 9781491934111
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Langue: anglais
Edité par Oreilly & Associates Inc, 2017
ISBN 10 : 1491934115 ISBN 13 : 9781491934111
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Ajouter au panierPaperback. Etat : Brand New. 300 pages. 9.25x7.00x0.50 inches. In Stock.
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Ajouter au panierPaperback. Etat : new. New Copy. Customer Service Guaranteed.
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Ajouter au panierPaperback. Etat : New. Data Science is booming thanks to R and Python, but Java brings the robustness, convenience, and ability to scale critical to today's data science applications. With this practical book, Java software engineers looking to add data science skills will take a logical journey through the data science pipeline. Author Michael Brzustowicz explains the basic math theory behind each step of the data science process, as well as how to apply these concepts with Java.You'll learn the critical roles that data IO, linear algebra, statistics, data operations, learning and prediction, and Hadoop MapReduce play in the process. Throughout this book, you'll find code examples you can use in your applications.Examine methods for obtaining, cleaning, and arranging data into its purest formUnderstand the matrix structure that your data should takeLearn basic concepts for testing the origin and validity of dataTransform your data into stable and usable numerical valuesUnderstand supervised and unsupervised learning algorithms, and methods for evaluating their successGet up and running with MapReduce, using customized components suitable for data science algorithms.
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Ajouter au panierEtat : New. Über den AutorrnrnMichael Brzustowicz is a physicist turned data scientist. After a PhD from Indiana University, Michael spent his post doctoral years at Stanford University where he shot high powered Xrays at tiny molecules. Jumpin.
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Ajouter au panierPaperback. Etat : New. Data Science is booming thanks to R and Python, but Java brings the robustness, convenience, and ability to scale critical to today's data science applications. With this practical book, Java software engineers looking to add data science skills will take a logical journey through the data science pipeline. Author Michael Brzustowicz explains the basic math theory behind each step of the data science process, as well as how to apply these concepts with Java.You'll learn the critical roles that data IO, linear algebra, statistics, data operations, learning and prediction, and Hadoop MapReduce play in the process. Throughout this book, you'll find code examples you can use in your applications.Examine methods for obtaining, cleaning, and arranging data into its purest formUnderstand the matrix structure that your data should takeLearn basic concepts for testing the origin and validity of dataTransform your data into stable and usable numerical valuesUnderstand supervised and unsupervised learning algorithms, and methods for evaluating their successGet up and running with MapReduce, using customized components suitable for data science algorithms.
Langue: anglais
Edité par O'reilly Media Jul 2017, 2017
ISBN 10 : 1491934115 ISBN 13 : 9781491934111
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
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Ajouter au panierTaschenbuch. Etat : Neu. Neuware - Data Science is booming thanks to R and Python, but Java brings the robustness, convenience, and ability to scale critical to today's data science applications. With this practical book, Java software engineers looking to add data science skills will take a logical journey through the data science pipeline. Author Michael Brzustowicz explains the basic math theory behind each step of the data science process, as well as how to apply these concepts with Java. You'll learn the critical roles that data IO, linear algebra, statistics, data operations, learning and prediction, and Hadoop MapReduce play in the process. Throughout this book, you'll find code examples you can use in your applications. Examine methods for obtaining, cleaning, and arranging data into its purest formUnderstand the matrix structure that your data should takeLearn basic concepts for testing the origin and validity of dataTransform your data into stable and usable numerical valuesUnderstand supervised and unsupervised learning algorithms, and methods for evaluating their successGet up and running with MapReduce, using customized components suitable for data science algorithms.
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Ajouter au panierTaschenbuch. Etat : Neu. Data Science with Java | Michael Brzustowicz | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2017 | O'Reilly Media | EAN 9781491934111 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
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Ajouter au panierpaperback. Etat : New. Paperback. Pub Date: 2020-04-01 Pages: 186 Language: Chinese Publisher: People Post Press Java real scientific data based on clear. object-oriented Java code. discussed some of the basic principles of scientific research data. Taking into account the desired item scalability. robustness and convenience. Java is an ideal .
Langue: anglais
Edité par Oreilly & Associates Inc, 2017
ISBN 10 : 1491934115 ISBN 13 : 9781491934111
Vendeur : Revaluation Books, Exeter, Royaume-Uni
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Ajouter au panierPaperback. Etat : Brand New. 300 pages. 9.25x7.00x0.50 inches. In Stock. This item is printed on demand.