Optimizing R Code with Rcpp
Offered By: DataCamp
Course Description
Overview
Use C++ to dramatically boost the performance of your R code.
R is a great language for data science, but sometimes the code can be slow to run. Combining the comfort of R with the speed of a compiled language
is a great way to reclaim the performance your code deserves.
C++ is a modern, high performance language that is simple enough to learn
in the context of accelerating R code. With the help of the Rcpp package,
C++ integrates very neatly with R. You will learn how to create and manipulate
typical R objects (vectors and lists), and write your own C++ functions
to dramatically boost the performance of your R code.
R is a great language for data science, but sometimes the code can be slow to run. Combining the comfort of R with the speed of a compiled language
is a great way to reclaim the performance your code deserves.
C++ is a modern, high performance language that is simple enough to learn
in the context of accelerating R code. With the help of the Rcpp package,
C++ integrates very neatly with R. You will learn how to create and manipulate
typical R objects (vectors and lists), and write your own C++ functions
to dramatically boost the performance of your R code.
Syllabus
- Introduction
- Writing, benchmarking, and debugging your first C++ code.
- Functions and Control Flow
- Writing functions, controlling the flow with if and else, and learning to use the three kinds of loops in C++.
- Vector classes
- Manipulate and compute with Rcpp and native C++ vectors.
- Case Studies
- Use random numbers and write algorithms for applied time series models.
Taught by
Team ThinkR
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