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Beginning Data Science in R
Thomas Mailund (Taschenbuch, Englisch)
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Beschreibung
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. Dieses Produkt haben wir gerade leider nicht auf Lager.
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Technische Daten
Erscheinungsdatum
13.03.2017
Sprache
Englisch
EAN
9781484226704
Herausgeber
APRESS
Sonderedition
Nein
Autor
Thomas Mailund
Seitenanzahl
352
Einbandart
Taschenbuch
Buch Untertitel
Data Analysis, Visualization, and Modelling for the Data Scientist
Autorenporträt
Thomas Mailund is an associate professor in bioinformatics at Aarhus University, Denmark. His background is in math and computer science but for the last decade his main focus has been on genetics and evolutionary studies, particularly comparative genomics, speciation, and gene flow between emerging species.
Schlagwörter
R, programming, statistics, data science, big data, machine learning, deep learning, ai, cloud, analytics, coding, software
Thema-Inhalt
UN - Datenbanken
UMC - Compiler und Übersetzer
Höhe
254 mm
Breite
17.8 cm
-.-
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