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Domain-Specific Languages in R

Advanced Statistical Programming

(Autor)

Buch | Softcover
257 Seiten
2019 | 1st ed.
Apress (Verlag)
978-1-4842-4004-5 (ISBN)
CHF 19,45 inkl. MwSt
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Gain an accelerated introduction to domain-specific languages in R, including coverage of regular expressions. This compact, in-depth book shows you how DSLs are programming languages specialized for a particular purpose, as opposed to general purpose programming languages. Along the way, you'll learn to specify tasks you want to do in a precise way and achieve programming goals within a domain-specific context.

Domain-Specific Languages in R includes examples of DSLs including large data sets or matrix multiplication; pattern matching DSLs for application in computer vision; and DSLs for continuous time Markov chains and their applications in data science. After reading and using this book, you'll understand how to write DSLs in R and have skills you can extrapolate to other programming languages.

What You'll Learn





Program with domain-specific languages using R

Discover the components of DSLs

Carry out large matrix expressions and multiplications

Implement metaprogramming with DSLs

Parse and manipulate expressions





Who This Book Is For


Those with prior programming experience. R knowledge is helpful but not required.

Thomas Mailund is an associate professor in bioinformatics at Aarhus University, Denmark. He has a background in math and computer science. For the last decade, his main focus has been on genetics and evolutionary studies, particularly comparative genomics, speciation, and gene flow between emerging species. He has published Beginning Data Science in R, Functional Programming in R and Metaprogramming in R with Apress as well as other books.

1: Introduction



2: Matrix Expressions



3: Components of a Programming Language



4: Functions, Classes, and Operators



5: Parsing and Manipulating Expressions



6: Lambda Expressions



7: Environments and Expressions



8: Tidy Evaluation



9: List Comprehension



10: Continuous-Time Markov Chains



11: Pattern Matching



12: Dynamic Programming



13: Conclusion

Erscheint lt. Verlag 22.2.2019
Zusatzinfo 10 Illustrations, black and white; IX, 257 p. 10 illus.
Verlagsort Berkley
Sprache englisch
Maße 155 x 235 mm
Themenwelt Mathematik / Informatik Informatik Programmiersprachen / -werkzeuge
Mathematik / Informatik Informatik Software Entwicklung
Mathematik / Informatik Informatik Theorie / Studium
Mathematik / Informatik Mathematik Angewandte Mathematik
Schlagworte AI • Big Data • course code • Deep learning • domain specific languages • DSLs • Embedded • programming • R language • R Programming • Statistics
ISBN-10 1-4842-4004-9 / 1484240049
ISBN-13 978-1-4842-4004-5 / 9781484240045
Zustand Neuware
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