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Data Science in R: A Case Studies Approach to Computational Reasoning and Problem Solving (Chapman & Hall/CRC The R Series)

Amazon.com Price:  $59.40 (as of 18/04/2019 22:25 PST- Details)

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Description

Effectively Access, Turn into, Manipulate, Visualize, and Reason about Data and Computation

Data Science in R: A Case Studies Approach to Computational Reasoning and Problem Solving illustrates the main points 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 products and services, Keyhole Markup Language (KML), and Google Earth
  • Statistical methods, such as classification trees, k-nearest neighbors, and naïve 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 in order that students gain valuable experience and data science skills. Students discover ways to acquire and work with unstructured or semistructured data in addition to 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 consider day by day computational tasks. It’ll fortify readers’ computational reasoning of real-world data analyses.


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