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Data Science with Java Vital Source e-bog
Michael R. Brzustowicz og PhD
(2017)
O'Reilly Media, Inc
471,00 kr.
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Data Science with Java
Practical Methods for Scientists and Engineers
Michael R. Brzustowicz
(2017)
Sprog: Engelsk
O'Reilly Media, Incorporated
543,00 kr.
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Detaljer om varen
- 1. Udgave
- Vital Source searchable e-book (Reflowable pages)
- Udgiver: O'Reilly Media, Inc (Juni 2017)
- Forfattere: Michael R. Brzustowicz og PhD
- ISBN: 9781491934067
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 form Understand the matrix structure that your data should take Learn basic concepts for testing the origin and validity of data Transform your data into stable and usable numerical values Understand supervised and unsupervised learning algorithms, and methods for evaluating their success Get up and running with MapReduce, using customized components suitable for data science algorithms
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Bookshelf online: 5 år fra købsdato.
Bookshelf appen: ubegrænset dage fra købsdato.
Udgiveren oplyser at følgende begrænsninger er gældende for dette produkt:
Print: -1 sider kan printes ad gangen
Copy: højest -1 sider i alt kan kopieres (copy/paste)
Detaljer om varen
- Paperback: 236 sider
- Udgiver: O'Reilly Media, Incorporated (Juni 2017)
- ISBN: 9781491934111
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 form
- Understand the matrix structure that your data should take
- Learn basic concepts for testing the origin and validity of data
- Transform your data into stable and usable numerical values
- Understand supervised and unsupervised learning algorithms, and methods for evaluating their success
- Get up and running with MapReduce, using customized components suitable for data science algorithms
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