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 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 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.
by S. Ventura Soto, Jose M. Luna, Alberto Cano (eds) - InTech
High volumes of valuable data are generated day by day in modern organizations. The management of huge volumes of data has become a priority in these organizations, requiring new techniques for data management and analysis in Big Data environments.
by Howard Besser - Getty Research Institute
The book allows curators, librarians, collection managers, students to better understand the processes involved in building a cohesive set of digital images. It also explores how to link digitized images to the information required to manage them.