Data science with Java : practical methods for scientists and engineers
Material type: TextPublication details: Mumbai : Shroff Publishers, 2017Edition: First editionDescription: xii, 220 pages : illustrationsISBN: 9781491934111; 9789352135738Subject(s): Java (Computer program language) | Data structures (Computer science)DDC classification: 005.133Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds |
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Lending Books | Main Library Stacks | REF | 005.133 BRZ (Browse shelf(Opens below)) | Available | 015582 |
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004.67 OAK Java EE applications on Oracle Java Cloud : | 004.67 RIT Cloud computing : implementation, management, and security | 004.68 SAN TCP/IP and NFS : | 005.133 BRZ Data science with Java : practical methods for scientists and engineers | 005.133 GIL Efficient R programming : a practical guide to smarter programming | 005.133 KOC Programming in C / | 005.133 SES AngularJS up and running / |
Originally published in Sebastopol, CA. by O'Reilly Media
Includes index.
Data I/O -- Linear algebra -- Statistics -- Data operations -- Learning and prediction -- Hadoop MapReduce -- Datasets.
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. --
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