SAMilt

SAMilt is an open-source software framework designed to help organizations build and deploy self-adapting intelligent systems, with a focus on processing streaming or time-series data. It provides a modular architecture that allows researchers and developers to combine online learning algorithms, drift detection methods, and ensemble techniques in a single workflow. The project emphasizes portability, cross-language bindings, and governance for production deployments.

Origins of SAMilt trace to a collaboration of researchers at several universities in the early 2010s, with the first public release in 2014. Since then it has undergone periodic updates and grown a user community. The architecture centers on a core runtime, a plugin system for data transformers, learning models, and evaluation and monitoring components. It supports online and incremental learning, automatic model selection under concept drift, and simulated data generation for testing.

Applications of SAMilt span finance, industrial IoT, and digital health, among others. It is used for real-time risk assessment, fault detection, and patient monitoring. The toolkit provides APIs for data ingestion from streams, model training, evaluation, deployment, and monitoring dashboards.

Development and licensing: SAMilt is maintained by an open-source community under a permissive license, with contributions coordinated through a central repository. Documentation covers installation, tutorials, and best practices for governance, security, and reproducibility.

See also: online learning, concept drift, streaming analytics, ensemble methods.