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Beginning data science in R: data analysis, visualization, and modelling for the data scientist

By: Mailund, ThomasMaterial type: TextTextPublication details: New York A Press  2021 Description: xxvii, 352 pISBN: 9781484240588Subject(s): Quantitative research | R (Computer program language) | Computer software--Development | Big data | Programming languages (Electronic computers) | Data miningDDC classification: 001.42 Summary: 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 Specifications
List(s) this item appears in: IT & Decision Sciences | Marketing
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Item type Current library Collection Call number Copy number Status Date due Barcode
Book Book Indian Institute of Management LRC
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IT & Decisions Sciences 001.42 MAI (Browse shelf(Opens below)) 1 Available 003902

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
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