Beginning data science in R 4 : data analysis, visualization, and modelling for the data scientist /

Discover best practices for data analysis and software development in R and start on the path to becoming a fully-fledged data scientist. Updated for the R 4.0 release, this book teaches you techniques for both data manipulation and visualization and shows you the best way for developing new softwar...

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Bibliographic Details
Call Number:Libro Electrónico
Main Author: Mailund, Thomas (Author)
Format: Electronic eBook
Language:Inglés
Published: New York, New York : Apress, [2022]
Edition:2nd ed..
Subjects:
R (Computer program language)
Statistics > Data processing.
R (Langage de programmation)
Statistique > Informatique.
Statistics > Data processing
Online Access:Texto completo (Requiere registro previo con correo institucional)
Table of Contents:
  • 1: Introduction
  • 2: Introduction to R Programming
  • 3: Reproducible Analysis
  • 4: Data Manipulation
  • 5: Visualizing Data
  • 6: Working with Large Data Sets
  • 7: Supervised Learning
  • 8: Unsupervised Learning
  • 9: Project 1: Hitting the Bottle
  • 10: Deeper into R Programming
  • 11: Working with Vectors and Lists
  • 12: Functional Programming
  • 13: Object-Oriented Programming
  • 14: Building an R Package
  • 15: Testing and Package Checking
  • 16: Version Control
  • 17: Profiling and Optimizing
  • 18: Project 2: Bayesian Linear Progression
  • 19: Conclusions.

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