PyCaret is an open-source, low-code machine learning library in Python. It is designed to streamline the process of training and deploying machine learning models with minimal effort. PyCaret simplifies the workflow by providing a consistent API and a wide range of built-in functions for model selection, preprocessing, feature engineering, and evaluation.

Features of PyCaret:

Provides an easy-to-use API for training and evaluating machine learning models.
Supports a wide range of machine learning algorithms, including classification, regression, clustering, and anomaly detection.
Automates tasks like feature scaling, missing value imputation, and encoding categorical variables.
Allows for model comparison and selection with a simple interface.
Provides tools for model interpretation and visualization of results.
Supports integration with popular libraries such as scikit-learn, XGBoost, and LightGBM.

To check the PyCaret version:
$ python -c "import pycaret; print(pycaret.__version__)"

Disclaimer: PyCaret is an open-source library distributed under the MIT license. It is provided "as is," without any warranty, express or implied. Users are responsible for following ethical guidelines and ensuring compliance with relevant regulations when using PyCaret for machine learning tasks.

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