There is a pro for Python in that it makes machine learning really easy, or at least incredibly accessible. You can write and test classifiers in about 5 lines of Python using scikit-learn. The second point is that virtually all the latest deep learning packages come with Python frontends by default nowadays. For stats you could also use SPSS.

The other advantage of Python is that as a scripting language it's very powerful for data wrangling and pre-processing, without needing all the boilerplate that e.g. C++ would require.

Julia is another option. You can even call R and python code from a Julia REPL.

You generally want an interactive language, though, because there is an iterative cycle in prototyping models.

They are not the only ones, but python is definitely the one which is likely to get you the most productivity fastest.

R and Python are not your only options. Check out the article for some other languages people are using.

R and Python are probably the two with the most support/community materials around them - lots of tutorials, libraries, guides etc.

Given that the article mentions many library implementations in Java, that puts JVM languages on the table. While Scala may be a good one, which the article mentions, that also puts Clojure on the table as well.

> don't relish the thought of using either language

Why not?

> only choices

Obviously not, according to the linked article. However, many people like Python and/or R. Perhaps you should find out why before dismissing their choices.