Why is Python Used For Machine Learning?

Python is used for machine learning because it combines remarkable power with very clear syntax and it’s relatively easy to learn.

Python has risen in popularity amongst data professionals over the past several years and is now one of the most popular programming languages for data science and machine learning.

Popularity aside, Python’s accessibility makes it a great option if you’re interested in breaking into the data field but don’t have much experience with object-oriented programming. Like many languages, Python can be used in web development projects to create websites and apps and is particularly useful for back-end development.

But unlike programming languages like HTML and Javascript, Python is best used for parsing data and is widely used within data science and machine learning using libraries like TensorFlow, SciPy, and Pandas, which offer packages for math, science, engineering, data analysis, and modeling.

A key benefit to using Python is that, again unlike other programming languages, it has a strong emphasis on readability. With that in mind, Python allows programmers to use English keywords for commands instead of punctuations. This makes it easier to write large chunks of code or build onto a current application without having to write more code. The readable features of Python make it easy to maintain and update.