Introduction to Data Science
by Jeffrey Stanton
Number of pages: 196
This book provides non-technical readers with a gentle introduction to essential concepts and activities of data science. For more technical readers, the book provides explanations and code for a range of interesting applications using the open source R language for statistical computing and graphics.
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by Michael R. Berthold (ed.) - Springer
The focus of this book, and the BISON project from which the contributions are originating, is a network based integration of various types of data repositories and the development of new ways to explore the resulting gigantic information networks.
by Mary-Jo Kline, Susan Holbrook Perdue - University of Virginia Press
In addition to exploring the role electronic technology plays in the editing process, this edition provides the most current treatment of the craft's fundamental issues. These include locating and collecting sources, transcribing source texts, etc.
by Kieran Greer
This book describes different aspects of knowledge-based networks and is important for future Internet / mobile-based information networks. This book combines Artificial Intelligence, service-based systems and distributed knowledge management.
by Jeroen Janssens - O'Reilly Media
This guide demonstrates how the flexibility of the command line can help you become a more productive data scientist. You'll learn how to combine small, yet powerful, command-line tools to quickly obtain, scrub, explore, and model your data.