Python is a high-level, open-sourced, programming language, first released in 1991. Python is often called the swiss army knife of coding as it is still the go-to language for programming projects, data mining, and data analytics. Even today it is the most popular, dynamic, versatile, interactive and the most relevant language.

In today's scene where search engines, personal assistants, and fraud detection systems, spam filters, recommendation systems, are all made possible by AI and machine learning, it requires coming up with algorithms that process information like a human.

Python practitioners believe that it is well-suited for AI and machine learning. Let's find out why is it still the most popular programming language for AI and ML.

Easy to read and simple

Python is both readable and simple. It is easy to learn, understand and code. It is easy to set up and has a wide range of applications. It is even being used in cloud services in some capacity or other. It is indeed a versatile language with simple syntax.

Platform Independence

Platform independence is a programming language or framework that allows developers to implement things on one machine and then use it on another machine without any (or with only minimal) changes. The key to Python's popularity is that it is a platform-independent language.

Python is supported by many platforms including Linux, Windows, and macOS. Thus, Python code can be used to create stand-alone executable programs which means that Python software can be easily distributed and can be used on different operating systems without a Python interpreter.

Developers often use services such as Google or Amazon for their computing needs. But there are many companies and data scientists who use their own machines with powerful Graphics Processing Units to train their ML models and Python being platform-independent makes it a lot cheaper and easier for these companies.

Big community and libraries

Learning programming languages is not easy without a support system. But with Python, you would easily find a solution to any of your Python-related problems in minutes. Python libraries have the best collection in machine learning and data science. Communities like TensorFlow, StackOverflow helps Python experts together to guide the newcomers.

Implementing AI and ML algorithms can be a challenge and require a lot of time. To reduce development time, programmers can refer to a number of Python frameworks and libraries. A software library is a pre-written code that developers use to solve common programming tasks and Python has an extensive set of libraries for artificial intelligence and machine learning.

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