Python has become the most widely used programming language today — especially in the world of data science because it is a high-performance language, easy to learn and debug, and has extensive library support. Each of these libraries has a particular focus. Some manage image and textual data, while others focus on data mining, neural networks, and data visualization. Python can be used for statistical analysis and building predictive models. When it comes to solving data science tasks and challenges, data enthusiasts, analysts, engineers, and scientists are leveraging the power of Python.

In this article, I will be talking about the top ten most useful Python libraries for data science and machine learning.

Some of the libraries have been installed if you are using the Anaconda distribution. All you have to do is import the library or install it with pip if it is not available on your machine.

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