• Contact
  • Newsletter
  • About us
  • Delivery options
  • News
    • PROSPERO
    'Language is english. Váltás magyarra.'
    Wishlist
    0
    Beginning Data Science in R 4: Data Analysis, Visualization, and Modelling for the Data Scientist

    Beginning Data Science in R 4 by Mailund, Thomas;

    Data Analysis, Visualization, and Modelling for the Data Scientist

      • GET 8% OFF

      • The discount is only available for 'Alert of Favourite Topics' newsletter recipients.
      • Publisher's listprice EUR 58.84

      • The price is estimated because at the time of ordering we do not know what conversion rates will apply to HUF / product currency when the book arrives. In case HUF is weaker, the price increases slightly, in case HUF is stronger, the price goes lower slightly.

         24 959 Ft (23 771 Ft + 5% VAT)
      • Discount 8% (cc. 1 997 Ft off)
      • Discounted price 22 963 Ft (21 869 Ft + 5% VAT)

    24 959 Ft

    db
    Add to wishlist

    Availability

    Estimated delivery time: In stock at the publisher, but not at Prospero's office. Delivery time approx. 3-5 weeks.
    Not in stock at Prospero.

    Why don't you give exact delivery time?

    Delivery time is estimated on our previous experiences. We give estimations only, because we order from outside Hungary, and the delivery time mainly depends on how quickly the publisher supplies the book. Faster or slower deliveries both happen, but we do our best to supply as quickly as possible.

    Product details:

    • Edition number 2nd ed.
    • Publisher Apress
    • Date of Publication 24 June 2022
    • Number of Volumes 1 pieces, Book

    • ISBN 9781484281543
    • Binding Paperback
    • No. of pages511 pages
    • Size 254x178 mm
    • Weight 1016 g
    • Language English
    • Illustrations 100 Illustrations, black & white
      • 423

    Categories

    Compilers and Interpreters High-level programming Programming in general

    Short description:

    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 software packages for R.

    Beginning Data Science in R 4, Second Edition 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

    More

    Long description:

    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 software packages for R. 

    Beginning Data Science in R 4, Second Edition 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. 

    Modern data analysis requires computational skills and usually a minimum of programming. After reading and using this book, you'll have what you need to get started with R programming with data science applications.  Source code will be available to support your next projects as well.

    Source code is available at github.com/Apress/beg-data-science-r4.


    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.

    More

    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.

    More
    Recently viewed
    previous
    Beginning Data Science in R 4: Data Analysis, Visualization, and Modelling for the Data Scientist

    Beginning Data Science in R 4: Data Analysis, Visualization, and Modelling for the Data Scientist

    Mailund, Thomas;

    24 959 HUF

    Parametric Modeling with SOLIDWORKS 2022

    Parametric Modeling with SOLIDWORKS 2022

    Shih, Randy H.; Schilling, Paul J.;

    31 884 HUF

    Practical Construction Planning and Control Using Microsoft Project: An Illustrative Guide

    Practical Construction Planning and Control Using Microsoft Project: An Illustrative Guide

    Aziz, Ahmed M. Abdel;

    46 556 HUF

    Language Change and Generative Grammar

    Language Change and Generative Grammar

    Brandner, Ellen; Ferraresi, Gisella; (ed.)

    23 326 HUF

    Diffusions, Markov Processes, and Martingales: Volume 1, Foundations

    Diffusions, Markov Processes, and Martingales: Volume 1, Foundations

    Rogers, L. C. G.; Williams, David;

    34 915 HUF

    Autodesk Revit for Architecture Certified User Exam Preparation (Revit 2020 Edition)

    Autodesk Revit for Architecture Certified User Exam Preparation (Revit 2020 Edition)

    Stine, Daniel John;

    19 737 HUF

    Design and Test Technology for Dependable Systems-on-Chip

    Design and Test Technology for Dependable Systems-on-Chip

    Ubar, Raimund; (ed.)

    82 719 HUF

    Parametric Modeling with SOLIDWORKS 2021

    Parametric Modeling with SOLIDWORKS 2021

    Shih, Randy H.; Schilling, Paul J.;

    31 378 HUF

    Quantum Random Number Generation: Theory and Practice

    Quantum Random Number Generation: Theory and Practice

    Kollmitzer, Christian; Schauer, Stefan; Rass, Stefan;(ed.)

    63 540 HUF

    Railway Noise and Vibration: Mechanisms, Modelling and Means of Control

    Railway Noise and Vibration: Mechanisms, Modelling and Means of Control

    Thompson, David;

    80 598 HUF

    next
    www.prospero.hu
    Facebook link for Prospero's books
    Log in Registration Have your data changed? Your Orders Basket Wishlist Invoices, payments Privacy Cookies About us News Your personal newsletter Contact
    Copyright © 2000-2025. All rights reserved. Prospero's Books