Machine Learning has developed vastly since its inception in the second half of the twentieth century. Today, it is being used in almost all industries – cybersecurity, manufacturing, healthcare, retail, education, etc. For Machine Learning to expand, it also requires a programming language that has the capacity to easily advance at the same pace. Python has come out as a winner in the race to become the most preferred language for Machine Learning.
Let’s understand what drives people to use Python for Machine Learning.
One of the main reasons Python is the most preferred language for Machine Learning is that the language is easy to use. The syntax of the language is not complicated and is used by beginners and expert developers. This allows developers to concentrate on solving the Machine Learning programs rather than focus their energy on understanding the language itself.
It is imperative that problems occurring in Machine Learning be solved quickly. Python, because of its popularity, has a large community of developers and supporters. Which simply means that Python has many libraries that can come to aid during a crisis.
Python as a programming language is very flexible. It allows developers to choose their own programming styles and even lets them combine styles to solve different problems in an efficient way.
Python’s flexibility and versatility are evident from the fact that it can run on any platform – Windows, macOS, Linux, Unix. Also, migrating programming data to different platforms is also handy.