5 Reasons For Python’s Popularity in Machine Learning

August 28, 2020

In recent years, the Python language has become increasingly popular among programmers at the world’s leading companies. In particular, many Machine Learning (ML) systems are now being developed using Python.

But why has Python assumed this leading role in the ML world?

Here are five reasons for this rise in popularity.

SIMPLICITY: Python is widely considered to be one of the easiest programming languages to learn, which makes it attractive to new ML programmers. In addition, even though Python has a relatively simple syntax, it is still a powerful language, which makes it a great choice for experienced ML developers as well.

READABILITY: As one might expect from its relative simplicity, Python code is clean and easy to understand. This helps programmers debug their code, and helps project managers understand the code created by their team members.

EXTENSIBILITY: Since Python has become one of the most popular programming languages, many packages, libraries, and modules have been developed for it. An incredible number of useful Python libraries are now freely available for anyone to use. (In 2019, one analysis put the total at “nearly 10,000 open source Python libraries.”) These libraries extend the programming power of the Python language. For example, PyTorch and SciKit-learn are two popular open-source Python libraries for ML applications.

Note that this is a kind of “positive popularity feedback loop”: the more popular Python becomes, the more packages are developed to extend its power, which then makes it even more popular. Machine Learning happens to be one area where such extensions to Python have proven particularly fruitful.

RELIABILITY: Another benefit of Python’s popularity is that it is now widely supported by many developers. The fact that Python is well supported means that the language is stable and reliable, and likely to stay that way for the foreseeable future.

LONGEVITY: The most popular programming languages tend to survive for years, or even decades. Hence, when project managers decide which language to use to create and deploy ML systems, Python is considered a worthwhile investment, because the popularity of this language gives it a strong seal of approval and a sense of security against becoming obsolete.

(Back when IBM was the dominant player in computer hardware, there was a popular saying: “No one ever got fired for buying IBM” – and in today’s world of ML software, you could replace “buying IBM” with “using Python.”)

Bottom line: Python’s current popularity should result in continued momentum to sustain further Python ecosystem growth — making it highly likely that Python will continue to be used and supported in ML applications for a long time to come.

By: Don Rose

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