/MonthOfJulia

Primary LanguageJupyter Notebook

Month of Julia

Julia is a high-performance platform for applying Functional Programming principles to statistical and scientific problems. Julia already has a large and growing user base, resulting in a diverse range of additional packages. It's a high high-level language, so relatively easy to learn and write (think Python). However, it has a sophisticated JIT compiler which results in execution speeds comparable to C and FORTRAN.

Julia logo

R is still my preferred tool for day to day analytical tasks but I can see that I will be dabbling more and more with Julia in the future.

Links to Blog Posts

The code in this repository was written to accompany a series of blog posts, which can be accessed here or directly via the list below. I'll apologise in advance that I have been sloppy in places and sometimes used the incorrect nomenclature. For instances, talking about "methods" when I should have said "functions", or "class" when I should have said "type". I trust that the intent will still be clear.

Acknowledgements

In the process of putting these notes together, I used the following invaluable references: