How Is Python Used In Machine Learning?

Artificial Intelligence and Machine Learning have transformed the industry. Both these concepts are no more a part of some sci-fi film. Instead, they have become the reality of today. While we talk so much about its use, there is also a great demand for AI and ML experts. To gain complete knowledge about these concepts and to use the same in real life, it is mandatory to have knowledge about a programming language that forms the base of the same. Python is considered to be apt for Machine Learning.

Why Python?

While there are so many programming languages in the world, there is a special emphasis on Python. Let's understand why so?

1. Ease of learning- One of the major reasons why Python is preferred over other languages is because it is easy to learn. When compared with Java or C++, the syntax is comparatively simpler in Python, which makes it easy to use.

2. Great choice of libraries- Another reason which makes Python a popular language for Machine Learning is because it offers a wide spectrum of libraries. Machine learning needs a lot of data processing, and with Python's libraries, you can easily access and transform a large volume of data.  

3. Flexibility- One of the notable features of Python is that it offers flexibility:  

• The developer can choose either description or OOPs

• Recompilation of source course is not required. Implementing change is easier in this

• Python can be easily combined with other languages 

4. Accessible across different platforms- One of the things that makes Python preferable is that you can run it on any platform like Linux, Windows, macOS, Unix, etc. In case there is a need to transfer it from one platform to another, only minor modifications are needed to create an executable form of code.