The fastest Julia algorithm was 30,249 times faster than the worst R! Check out how the others approaches compare! Calling other languages in your R programming code is easy. In this tutorial, we made use of Julia programming language directly in R to see if it could accelerate our code. We contrast 5 different algorithms and talk about when you should (or should not!) use them. Subscribe to learn more about RStats and how you can make your code faster. 👀
00:00 Introduction and dataset
01:26 Setting up Julia
02:18 1st approach: Growing a vector with for loops & translating R code to Julia code
06:57 2nd approach: Dataframe pre-allocation
08:25 3rd approach: Lists - vectorization
10:04 4th approach: Linear algebra - matrices
11:35 5th approach: Dataframe manipulation
13:29 Global all-approach benchmarking
🐱 Get the code here: https://github.com/MaximeRivest/dds/blob/master/Can%20Julia%20really%20make%20your%20R%20code%20faster.R
🏎️ R performance playlist • R Programming - Performance
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