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Data Science with Java
Practical Methods for Scientists and Engineers
Taschenbuch von Michael Brzustowicz
Sprache: Englisch

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Beschreibung
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
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
Über den Autor

Michael 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. Jumping ship from academia, he worked at many startups (including his own) and has been pioneering big data techniques all the way. Michael specializes in building distributed data systems and extracting knowledge from massive data. He spends most of his time writing customized, multithreaded code for statistical modeling and machine learning approaches to everyday big data problems. Michael now teaches Big Data, parttime, at the University of San Francisco.

Details
Erscheinungsjahr: 2017
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Seiten: 236
Inhalt: Kartoniert / Broschiert
ISBN-13: 9781491934111
ISBN-10: 1491934115
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Brzustowicz, Michael
Hersteller: O'Reilly Media
Abbildungen: Illustrations, black and white
Maße: 231 x 177 x 20 mm
Von/Mit: Michael Brzustowicz
Erscheinungsdatum: 18.07.2017
Gewicht: 0,416 kg
preigu-id: 109381509
Über den Autor

Michael 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. Jumping ship from academia, he worked at many startups (including his own) and has been pioneering big data techniques all the way. Michael specializes in building distributed data systems and extracting knowledge from massive data. He spends most of his time writing customized, multithreaded code for statistical modeling and machine learning approaches to everyday big data problems. Michael now teaches Big Data, parttime, at the University of San Francisco.

Details
Erscheinungsjahr: 2017
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Seiten: 236
Inhalt: Kartoniert / Broschiert
ISBN-13: 9781491934111
ISBN-10: 1491934115
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Brzustowicz, Michael
Hersteller: O'Reilly Media
Abbildungen: Illustrations, black and white
Maße: 231 x 177 x 20 mm
Von/Mit: Michael Brzustowicz
Erscheinungsdatum: 18.07.2017
Gewicht: 0,416 kg
preigu-id: 109381509
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