Discover best practices for data analysis and software development in R and start on the path to becoming a fully-fledged data scientist. This book teaches you techniques for both data manipulation and visualization and shows you the best way for developing new software packages for R.
Beginning Data Science in R details how data science is a combination of statistics, computational science, and machine learning. You’ll see how to efficiently structure and mine data to extract useful patterns and build mathematical models. This requires computational methods and programming, and R is an ideal programming language for this.
This book is based on a number of lecture notes for classes the author has taught on data science and statistical programming using the R programming language. Modern data analysis requires computational skills and usually a minimum of programming.
What You Will Learn
Perform data science and analytics using statistics and the R programming language
Visualize and explore data, including working with large data sets found in big data
Build an R package
Test and check your code
Practice version control
Profile and optimize your code
Who This Book Is For
Those with some data science or analytics background, but not necessarily experience with the R programming language.
Peace-Building by, between, and beyond Muslims and Evangelical Christians When Evangelical Christian and Muslim scholars meet to dialogue, to explore the interface between their perspectives, and to deepen the shared understandings, common resources, and relationships, they discover that they have much to talk about.
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Liquid Crystal Display Drivers: Techniques and Circuits
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Neural Networks: A Comprehensive Foundation (2nd Edition)
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