Artificial intelligence (AI) has a subfield called machine learning that enables computers to autonomously carry out tasks without being explicitly programmed and learn from experience. Python is a coding language used in programming and is distinguished by its simplicity, wide variety of uses, and extensive feature set.

To speed up ML processes, Python in ML uses a variety of Python machine learning libraries, which have the tools and functions to scale mathematical and scientific calculations. By using these frameworks, programmers may build machine learning models more quickly without having to master all the specifics of the underlying techniques. Let’s focus on the top 10 Python libraries in 2023.

This open-source, free software library is used to carry out mathematical computations. The Google Brain research team created this vast math library 2015 for large systems and neural network applications. The library supports Bayesian models and other probabilistic methods, and it provides users with access to several distribution functions such as Bernoulli, Chi2, and Gamma.

Scalability, improved graphical representations, regular upgrades and feature releases, simple library administration, and interoperability with GPU and ASIC are all advantages of TensorFlow. Moreover, TensorFlow is widely used by organizations like Airbnb, PayPal, and Twitter.

source:https://www.analyticsinsight.net/10-python-machine-learning-libraries-you-must-know-in-2023/