Languages
Mailund, Thomas.
Overview
Works: | 2 works in 12 publications in 1 languages |
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Titles
Beginning data science in R 4 = data analysis, visualization, and modelling for the data scientist /
by:
Mailund, Thomas.; SpringerLink (Online service)
(Electronic resources)
Pointers in C programming = a modern approach to memory management, recursive data structures, strings, and arrays /
by:
Mailund, Thomas.; SpringerLink (Online service)
(Electronic resources)
R data science quick reference = a pocket guide to APIs, libraries, and packages /
by:
Mailund, Thomas.; SpringerLink (Online service)
(Electronic resources)
Introducing Markdown and Pandoc = using markup language and document converter /
by:
Mailund, Thomas.; SpringerLink (Online service)
(Electronic resources)
Introduction to computational thinking = problem solving, algorithms, data structures, and more /
by:
Mailund, Thomas.; SpringerLink (Online service)
(Electronic resources)
Functional programming in R 4 = advanced statistical programming for data science, analysis, and finance /
by:
Mailund, Thomas.; SpringerLink (Online service)
(Electronic resources)
Functional programming in R = advanced statistical programming for data science, analysis and finance /
by:
Mailund, Thomas.; SpringerLink (Online service)
(Electronic resources)
R 4 data science quick reference = a pocket guide to APIs, libraries, and packages /
by:
Mailund, Thomas.; SpringerLink (Online service)
(Electronic resources)
Beginning data science in R = data analysis, visualization, and modelling for the data scientist /
by:
Mailund, Thomas.; SpringerLink (Online service)
(Electronic resources)
The joys of hashing = hash table programming with C /
by:
Mailund, Thomas.; SpringerLink (Online service)
(Electronic resources)
Functional data structures in R = advanced statistical programming in R /
by:
Mailund, Thomas.; SpringerLink (Online service)
(Electronic resources)
String algorithms in C = efficient text representation and search /
by:
Mailund, Thomas.; SpringerLink (Online service)
(Electronic resources)
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Subjects
Software Engineering.
Data structures (Computer science)
Application program interfaces (Computer software)
Computer Science, general.
Python.
Computer algorithms.
Hashing (Computer science)
Programming Language.
Quantitative research.
Data-driven Science, Modeling and Theory Building.
Programming Techniques.
Data Structures.
Professional Computing.
Python (Computer program language)
Algorithm Analysis and Problem Complexity.
Programming Languages, Compilers, Interpreters.
R (Computer program language)
Algorithms.
Data Mining and Knowledge Discovery.
Big Data.
Document markup languages.
Functional programming (Computer science)
Mathematical statistics- Computer programs.
C (Computer program language)
Web Development.
Machine Learning.
Computer Science.
Probability and Statistics in Computer Science.
Markdown (Document markup language)
Statistics- Data processing.
Computer programming.
Open Source.
Compilers and Interpreters.