When is R better than Python for machine learning projects?

Any team considering a project in machine learning should take its time to carefully consider whether they should choose R or Python. Although Python is currently the most popular programming language in the domain, there’s a certain number of advantages, found in R.

Reason why R is super useful

First, it’s a statistics-only language. For the teams who only deal with this kind of tasks, it’ll be easier to navigate here and move forward with their pipelines, without the distractions from all those models they might never need to use anyway.

Second, R offers robust capabilities for data analytics and visualization. If this is what you need to deal with, pick this language.

Third, if you just want to explore a couple of concepts without major investments of time and effort, R is much easier to use for early-stage prototyping.

When choosing R as the language for your ML project, you need to make sure you won’t need to roll out lots of additional components in the years to come, such as UI, API and others. Because if you might need these modules, you should seriously consider picking Python instead.