There are many problems to convert as a Machine Learning problem and probably you have heard about different programming languages. The most famous of them are Python and R, and I can understand if you feel stuck between choosing the right programming language for your project. My Bachelor’s Degree in Statistics which means that I am familiar with R. After decided to meet with Machine Learning I got some confusion about which programming language is better than the other. However, there is an important point to remember is that both languages have developed in order to help data scientists to perform analytical work easily.

As you know there are a lot of Data Scientist positions and if you do search through Linkedin, Indeed, Glassdoor… etc. you can be able to see them and of course the mandatory features for becoming a Data Scientist. R and Python are the most popular tools used by Data Scientist. I will be explaining both languages in this article.

## Python

Python is open-source and it has a reputation in machine learning because more concerned with predictive accuracy. Also, some majority of deep learning research is done in Python using Keras and PyTorch. Let’s look deeply;

- If your expectation of the project is more than statistical analysis, Python would be a better language because it includes less statistical model packages than R. But, of course, Python has packages like Numpy and Pandas for analyzing and modeling data.
- Python has better integration. For example, if you know other languages such as C, C#, or Java too, you can understand more easily and join different components with Python.
- What about the speed? Yes, for it, Python is not the best option unfortunately.
- Another topic is the library. As you know, Python has some of the most popular ML packages such as Scikit-learn in today’s world and the Scikit-learn is the powerful one. I can say is that Python would be fit well with the Machine Learning project with this library.

## R

R is an open-source language and focuses more on the statistical analysis and visualization of data. R language contains mathematical computations involved in machine learning which is derived from statistics, that is why it becomes the right choice in order to gain an understanding of the details. Let’s look deeply;

- If your expectation of the project is about statistical analysis and visualization of data, you are in the right place! Basic data management tasks are very easy because R was written by statisticians. As you know, data preparation is a crucial step before taking action and mostly we need to deal with labeling, filling missing values. Therefore, R which emphasizes user-friendly data analysis, statistics, and graphical models comes to the stage.
- R can perform complex computations really fast.
- R has its own packages for Machine Learning, too. Its most famous package is called Caret and it helps to create predictive models efficiently.
- What about integration? Integration could be challenged because R has difficult syntax.

## Conclusion

Both R and Python have their own advantages. The choice depends on you, just choose which programming language you want to go.

*References*

*https://www.educative.io/edpresso/machine-learning-python-vs-r*

*https://opensource.com/article/16/11/python-vs-r-machine-learning-data-analysis*

Like!! Great article post.Really thank you! Really Cool.

Thank you!