AutoML (Automated Machine Learning) is a framework designed to streamline and automate the end-to-end process of applying machine learning to real-world problems. It reduces the manual effort involved in data preprocessing, model selection, hyperparameter tuning, and evaluation, making it accessible to both experts and non-experts.

AutoML systems are capable of intelligently selecting algorithms, optimizing them, and evaluating performance using advanced search techniques and heuristics. Popular platforms include Google's AutoML, H2O.ai, Auto-sklearn, and Microsoft Azure AutoML.

Features of AutoML:

Automatic data preprocessing and feature engineering.
Model selection and hyperparameter optimization.
Support for classification, regression, and time series tasks.
Integrations with popular ML libraries such as scikit-learn, TensorFlow, and PyTorch.
Visual and code-based interfaces for different user skill levels.
Export of trained models for deployment in production environments.

To check if AutoML is installed and working in your environment, you can run:
$ pip list | grep automl
$ python -m automl --help (command varies based on the AutoML framework)

Disclaimer: AutoML tools are released under various open-source and commercial licenses. Users must adhere to the terms and conditions set by each framework's maintainers. It is recommended to consult the official documentation of the specific AutoML solution in use for configuration, usage instructions, and updates. The developers are not liable for any misuse or outcomes resulting from improper use.

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