Simulation for Data Science with R

High performance computing

Initially, it is important to measure which lines of code take the most computation time. Here, you should try to solve problems with the processing time of individual calculations by improving the computation time. This can often be done in R by vectorization, or often better by writing individual pieces of code in a compilable language, such as C, C++*, or Fortran**.

In addition, some calculations can be parallelized and accelerated through parallel computing.

Profiling to detect computationally slow functions in code

Take an example where you have written code for your data analysis but it runs (too) slow. However, it is most likely that not all your lines of code are slow and only a few lines need improvement in terms ...