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Publicado por O'Reilly Media 6/22/2017, 2017
ISBN 10: 1491934115 ISBN 13: 9781491934111
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Añadir al carritoPaperback or Softback. Condición: New. Data Science with Java: Practical Methods for Scientists and Engineers. Book.
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Añadir al carritoPaperback. Condición: 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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Publicado por O'Reilly Media 2016-04-25, 2016
ISBN 10: 1491934115 ISBN 13: 9781491934111
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Añadir al carritoPaperback. Condición: 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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Publicado por O'Reilly Media, Inc, USA, 2017
ISBN 10: 1491934115 ISBN 13: 9781491934111
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Publicado por Oreilly & Associates Inc, 2017
ISBN 10: 1491934115 ISBN 13: 9781491934111
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Añadir al carritoCondición: 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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Añadir al carritoPaperback. Condición: 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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Añadir al carritoPaperback. Condición: 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.
Idioma: Inglés
Publicado por O'reilly Media Jul 2017, 2017
ISBN 10: 1491934115 ISBN 13: 9781491934111
Librería: AHA-BUCH GmbH, Einbeck, Alemania
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Añadir al carritoTaschenbuch. Condición: 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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Añadir al carritoTaschenbuch. Condición: 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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Añadir al carritopaperback. Condición: 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 .
Idioma: Inglés
Publicado por Oreilly & Associates Inc, 2017
ISBN 10: 1491934115 ISBN 13: 9781491934111
Librería: Revaluation Books, Exeter, Reino Unido
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Añadir al carritoPaperback. Condición: Brand New. 300 pages. 9.25x7.00x0.50 inches. In Stock. This item is printed on demand.