GitHub - NannyML/nannyml: Detecting silent model failure. NannyML estimates performance for regression and classification models using tabular data. It alerts you when and why it changed. It is the only open-source library capable of fully capturing the impact of data drift on performance. - discu.eu

Linking pages

Don't be Fooled by Data Drift | ML Monitoring Tools https://www.nannyml.com/blog/when-data-drift-does-not-affect-performance-machine-learning-models 27 comments
GitHub - EthicalML/awesome-production-machine-learning: A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning https://github.com/EthicalML/awesome-production-machine-learning 0 comments
GitHub - kelvins/awesome-mlops: A curated list of awesome MLOps tools https://github.com/kelvins/awesome-mlops 0 comments
Predict Your Model’s Performance (Without Waiting for the Control Group) | by Samuele Mazzanti | Towards Data Science https://towardsdatascience.com/predict-your-models-performance-without-waiting-for-the-control-group-3f5c9363a7da 0 comments

Linked pages

GitHub - microsoft/LightGBM: A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks. https://github.com/Microsoft/LightGBM 11 comments

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