Python: Pros and cons for your project

If you are considering Python as a programming language for your project in machine learning, you should understand that it is – just like any other programming language under the sun – with its strengths and weaknesses. Python is probably the best pick as compared to all other viable alternatives available on the market, such as R, but not always.


It’s easy to master and code since it’s a general-purpose language with a focus on elegance and simplicity.

There’s a great number of libraries and frameworks here, which will enable you to cut down the time and effort you need to invest in your development ventures.

A great community around the language will simplify your process to hire new contributors to your project whenever you decide to grow your dev team.


There’s not as many statistical model packages as in R, so if your project is all about statistics, you should consider R instead.

There’s a certain set of problems you’ll face with regard to threading due to use of GIL here, but if you learn to do multiprocessing well, you’ll survive and flourish.