PyCaret is an open-source, low-code machine learning library in Python that automates the process of model selection, training, and deployment. It is designed to streamline the machine learning workflow with minimal effort, making it easier for data scientists and analysts to build and deploy models quickly.

Features of PyCaret:

• Automates machine learning workflows, including data preprocessing, model selection, training, and evaluation.
• Supports various machine learning tasks such as classification, regression, clustering, and anomaly detection.
• Integrates with popular libraries like scikit-learn, XGBoost, LightGBM, and TensorFlow.
• Easy-to-use API for both beginners and experienced data scientists.
• Works with Jupyter Notebooks and can export models for deployment in different environments.

To check version of PyCaret:

pip show pycaret

Disclaimer: PyCaret is an open-source machine learning library developed by the PyCaret community. It is distributed under the MIT license and is freely available for use and modification. This information is for educational purposes only and is not affiliated with, endorsed by, or sponsored by the PyCaret development team. PyCaret is provided "as is," without any warranty, express or implied. Users utilize this software at their own risk.