Why you should use Python for machine learning | Tech News

What is it about Python—the language, the ecosystem, the development processes around them—that has made it into such a favorite for data science?

Python has long enjoyed growing popularity in many areas of software development—scripting and process automation, web development, general applications. More recently it has become a leading language in machine learning. In this article we’ll look at the four major reasons why Python has become a juggernaut in that field.

Python keeps programming simple

The first major reason is of a piece with why Python has become a general success story: the language makes things simple and keeps them simple.

When Python was first developed, a major goal of the language was to be easy to both write and read. Code is read far more often than it’s written, especially in environments where it changes hands from one team to another. If you’re inheriting a machine learning application from another developer, especially one that makes use of multiple third-party components or has a good deal of custom business logic, it helps to have it written in a language that adds as little extra cognitive overhead as possible. Good Python code will have that quality, even more so than other languages.

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