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Data Science in R: A Case Studies Approach to Computational Reasoning and Problem Solving

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by Deborah Nolan & Duncan Temple Lang
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Data Science in R: A Case Studies Approach to Computational Reasoning and Problem Solving by Deborah Nolan & Duncan Temple Lang

Effectively Access, Transform, Manipulate, Visualize, and Reason about Data and Computation

Data Science in R: A Case Studies Approach to Computational Reasoning and Problem Solving illustrates the details involved in solving real computational problems encountered in data analysis. It reveals the dynamic and iterative process by which data analysts approach a problem and reason about different ways of implementing solutions.

The book's collection of projects, comprehensive sample solutions, and follow-up exercises encompass practical topics pertaining to data processing, including:

  • Non-standard, complex data formats, such as robot logs and email messages
  • Text processing and regular expressions
  • Newer technologies, such as Web scraping, Web services, Keyhole Markup Language (KML), and Google Earth
  • Statistical methods, such as classification trees, k-nearest neighbors, and na├»ve Bayes
  • Visualization and exploratory data analysis
  • Relational databases and Structured Query Language (SQL)
  • Simulation
  • Algorithm implementation
  • Large data and efficiency

Suitable for self-study or as supplementary reading in a statistical computing course, the book enables instructors to incorporate interesting problems into their courses so that students gain valuable experience and data science skills. Students learn how to acquire and work with unstructured or semistructured data as well as how to narrow down and carefully frame the questions of interest about the data.

Blending computational details with statistical and data analysis concepts, this book provides readers with an understanding of how professional data scientists think about daily computational tasks. It will improve readers' computational reasoning of real-world data analyses.To view this DRM protected ebook on your desktop or laptop you will need to have Adobe Digital Editions installed. It is a free software. We also strongly recommend that you sign up for an AdobeID at the Adobe website. For more details please see FAQ 1&2. To view this ebook on an iPhone, iPad or Android mobile device you will need the Adobe Digital Editions app, or BlueFire Reader or Txtr app. These are free, too. For more details see this article.

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Ebook Details
Pages: 539
Size: 71.6 MB
Publisher: CRC Press
Date published:   2015
ISBN: 9781482234824 (DRM-PDF)

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This product is listed in the following categories:

Nonfiction > Mathematics > Probability & Statistics
Nonfiction > Business & Economics > Statistics
Nonfiction > Computers > Database Management > Database Mining

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