If Python is not the best language for Data Science/Machine Learning? What is?
DISCLAIMER: There is nothing like ‘the best language for machine learning’.
Your best language depends on your background, what you plan on using machine learning for and why you are involved in the project in the first place. For example, front end web developers extend their use of JavaScript to machine learning.
Well, that is the end of this article. For more clarification, keep on scrolling down, slowly.
By the way, in previous articles, the meanings of data science and machine learning have been covered here and here respectively.
Which is the most popular language for machine learning?
Well, as previously stated, there is no singular ‘best’ language for machine learning but there is definitely the most used language for machine learning out of the languages commonly used.
Unsurprisingly, the most popular language for machine learning is PYTHON, with almost 60% of machine learning engineers preferring to code in python than other languages. Python has a number of advantages over others which make it the most popular language used in machine learning.
Advantages of using machine learning
· It has easy, readable and simple syntax
Python is written in plain English which makes it relatively easy to understand to a layman. This is one of the many reasons why python is recommended as a language to beginners.
· It is free to use and open source
Python has an OSI approved open license, so it is freely usable and also for commercial purposes.
· It has great libraries
A python library is a bundle of code, reusable codes and functions. It makes the code easier to write and less bulky. Examples of libraries are Numpy, Pandas, Matplotlib, Seaborn. The last two are great data visualization tools. The libraries are not also limited to the four that were just mentioned.
· Great community for beginner developers:
Python has a large and exponentially growing number of users worldwide.
Other languages commonly used for machine learning include;
R: This used when the project contains statistics mostly. Used for analysis and visualizations of data
C/C++: This is used more for Artificial intelligence for games
Java: Used more when working on network security and fraud detection.
JavaScript, Matlab, Ruby, Scala, SAS are other examples of languages used in machine learning.
