Domain-Specific Languages in R [electronic resource] : Advanced Statistical Programming /
Mailund, Thomas.author.
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. You will: 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 .
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.
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. You will: 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 .
Programming languages (Electronic computers).
Artificial intelligence.
Computer programming.
Mathematical statistics.
Big data.
R (Computer program language).
Programming Languages, Compilers, Interpreters.
Artificial Intelligence.
Programming Techniques.
Probability and Statistics in Computer Science.
Big Data.