Requirements: .ePUB, .PDF, .MOBI/.AZW reader, 10,6 MB
Overview: Welcome to “R Programming for Data Science”, a comprehensive guide that will take you on a journey from the basics of R programming to advanced techniques for working with data in the context of Data Science. As someone interested in Data Science, you’re likely aware of the importance of having a strong foundation in programming and data manipulation skills. This book aims to provide you with just that, using R as the primary tool for exploring and analyzing data. R has emerged as one of the most popular languages for data analysis and visualization, and for good reason. Its flexibility, ease of use, and extensive library of packages make it an ideal choice for anyone looking to extract insights from large datasets. Whether you’re a student, researcher, or professional in the field of Data Science, R is an essential tool that will help you get the job done. This book is designed to be both comprehensive and accessible, covering topics such as data types, visualization, statistical modeling, and Machine Learning. You’ll learn how to work with datasets, manipulate and transform data, create visualizations, and build predictive models using popular R packages like dplyr, tidyr, ggplot2, caret, and more. Throughout the book, we’ll focus on practical applications of R programming concepts, using real-world examples and case studies to illustrate key ideas. You’ll also learn how to troubleshoot common errors, work with missing data, and optimize your code for efficiency. This book is intended for anyone interested in Data Science, regardless of their prior programming experience.
Genre: Non-Fiction > Tech & Devices
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