Python is a high-level and general-purpose programming language. Python is also an interpreted programming language, and interpreters are available for almost all operating systems. Python was created in 1980 and released in 1991 by Guido van Rossum. The latest and stable version of Python currently available is Python 3.9.0. Python is a multi-paradigm programming language. Because object-oriented and structured programming are fully supported, and many of its features are support functional programming.
Python becomes one of the most popular languages worldwide because of its simplicity, less-cluttered syntax, and grammar. It is said to be an easily readable programming language. Now Python is also a preferred language by data scientists. According to the pool result published by KDnuggets in 2018, Python becomes the most popular language for data science and machine learning. Let’s see why its the most popular for machine learning and the fastest-growing programming language:
Readability and complexity:
If you look at the Python language philosophy, you will see that the language was built for its readability and less complexity. Anyone who knows basic programming of any other languages will understand Python program/code very fast written by other programmers. For example:
- C “Hello, World!” Program
#include <stdio.h>
Int main()
{
printf(“Hello, World!”);
return 0;
}
Output: Hello, world!
- Java “Hello, World!” Program
class Main{
public static void main(String[] args) {
System.out.println(“Hello, World!”);
}
}
Output: Hello, World!
- Python “Hello, World!” Program
print(“Hello, World!”)
Output: Hello, World!
From the given examples, you see the difference between C, Java, and Python programming languages. You can read those “Hello, World” programs and can understand what’s happening and why Python programming language is easily readable, and syntax is not much complex.
Powerful and easy implementation:
Students and researchers need to collect a large amount of data from different sources and process, define, clean, and organize them. Then they need to understand the data to develop the model. They also need to know the language well before implementing it. You may know Python is considered a beginner’s language, and anyone with basic knowledge can work with it. Compared to other programming languages, implementation of the model using Python is time-saving. So a developer can spend time on algorithms and learning related to machine learning.
Ease of powerful libraries and free tutorials:
Python comes with a large number of powerful libraries for machine learning. Tensorflow, PyTorch, Scikit-Learn, Matplotlib, Numpy, Keras, OpenCV, Pandas, etc., are some popular machine learning libraries. A large number of free learning resources and tutorials are also available online.
The End:
Most ML scientists prefer Python for machine learning because of its simplicity, easiness, readability, and powerful libraries. New ML libraries are available for free in GitHub build by other researchers or developers. Deep learning frameworks are also available with Python APIs. Python is not only used for data science but also for web development, desktop GUIs, software development, business application, etc. Python gains people’s hearts and popularity so fast because of its easiness, versatility, and readability.