Python offers a wide range of library modules and frameworks, making it one of the most compatible languages for constructing machine learning models and working on data science projects.

This article aims to provide some cool modules to utilize for your machine learning and data science projects apart from the standard libraries that are used.

The most commonly used python modules include numpy for numerical operations, scipy for scientific operations for dealing with something like sparse matrices, pandas to view the datasets in an organized manner, matplotlib and seaborn to visualize the data, analysis, and graphs of models constructed.

You can also utilize the scikit-learn module in python for the development of machine learning models through the various algorithms options available in the sklearn library. Also, you construct deep learning models by making use of frameworks such as TensorFlow and Pytorch.

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