Python vs R for machine learning, Best language for Machine Learning

Best Language for Machine Learning

Before starting the comparison for the best language for machine learning, let me clear some stuff. These are solely my opinions backed by intensive research and practical work. This is not a Partial opinion based on any language or biased to any one language. So lets begin the comparison.


Python dominates the scene when it comes to machine learning languages, and it will continue to do so for the next several years making it one of the most common machine learning programming languages. For machine learning, its adaptability makes it suitable. In addition, with more than 50 percent of machine learning engineers using Python, its syntactic simplicity makes it beginner-friendly language.


is one of the languages created specifically for the visualisation of data and statistics. In machine learning and data science, that is one of thekey reasons for its increasing popularity. The language is kept current and new with help from the open source community. Not only is it simple to create machine learning algorithms with R, but it also paves the way for the development of statistical 
visualization for those studio algorithms.

Talks About Syntax:-

If you will check the syntax for both the language,you will notice python is easier. The syntax for python is pretty easy and short. It can be understand by a normal guy with english language knowledge. Whereas the R syntax are much filld with symbols and numbers which makes it a bit difficult.

Community support

This is one of the most important topic of programming language which people neglect. Having a huge community of specific thing help to improve its worth and also solve each others problem quickly. With huge communiy of python it is very to find a solution to your problem, because hundreds of people have already faced that problem. So you are just few clicks away from your solution.

R also has its communities, where populer one is R-Ladies. It also have various data scientist fromdiverse background which makes it very helpfull in this field.


As this walkthrough proves, either language may be used as the sole data analysis method. In syntax and approach, both languages have lot of similarities, and you can not go wrong with either one. Ultimately, you can end up having to learn Python and so that you can use the 
strengths of both languages, choosing one or the other depending on your needs on per project basis. And learning both also makes you more versatile work applicant if you are searching for place in the Machine Learning and Data Science world.

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