Scikit-learn is a powerful open-source machine learning library for Python. It provides simple and efficient tools for data mining, data analysis, and modeling. Built on top of NumPy, SciPy, and matplotlib, it is designed to interoperate well with the broader Python scientific ecosystem.

Features of Scikit-learn:

• Offers a wide range of supervised and unsupervised learning algorithms such as classification, regression, clustering, and dimensionality reduction.
• Provides utilities for model selection, cross-validation, and performance metrics.
• Includes tools for preprocessing data, including feature scaling, encoding, and imputation.
• Built to work seamlessly with NumPy arrays and pandas DataFrames for flexible data handling.
• Supports pipelines and grid searches to streamline model building and tuning workflows.
• Well-documented and widely adopted in both academic and commercial machine learning projects.

To check the installed version of Scikit Learn, run these commands in your environment:

$ sudo su
$ sudo apt update
$ cd /opt
$ sklearn-python -c 'import sklearn; print(sklearn.__version__)'

Disclaimer: Scikit-learn is open-source software released under the BSD License. It is maintained by an active community of contributors. Users are responsible for ensuring the correct use of the library in their applications. The developers do not take responsibility for any consequences arising from the use of the software. Always refer to the official documentation for the most up-to-date and accurate information.