2 min read · Dec 23, 2023
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Python has become a popular programming language for machine learning due to its simplicity, readability, and powerful libraries. However, with multiple versions of Python available, it can be challenging for beginners to decide which version is best suited for machine learning. In this article, we will explore the different Python versions commonly used in the machine learning community and discuss their strengths and weaknesses.
Python 2 vs. Python 3
Python 2 and Python 3 are the two major versions of Python, and they have some significant differences that can impact machine learning projects. Python 2 was first released in 2000, while Python 3 was introduced in 2008 with the goal of improving the language and eliminating some of the design flaws of Python 2.
Although Python 2 is still in use in some legacy projects, it is best to choose Python 3 for new machine learning projects. Python 3 has better Unicode support, improved syntax, and several other language enhancements. Additionally, Python 3 is more actively maintained, with new features and bug fixes being regularly released.
Python 3.7, 3.8, and 3.9
Within Python 3, there are several versions to choose from. Python 3.7 was released in 2018, Python 3.8 in 2019, and Python 3.9 in 2020. Each new version brings improvements, bug fixes, and new features. When deciding which Python version to use for machine learning, it is essential to…