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NannyML is an open-source python library that allows you to estimate post-deployment model performance (without access to targets), detect data drift, and intelligently link data drift alerts back to changes in model performance. Built for data scientists, NannyML has an easy-to-use interface, interactive visualizations, is completely model-agnostic and currently supports all tabular classification use cases. Regression coming soon. The core contributors of NannyML have researched and developed a novel algorithm for estimating model performance: confidence-based performance estimation (CBPE). The nansters also invented a new approach to detect multivariate data drift using PCA-based data reconstruction.If you like what we are working on, be sure to become an Nanster yourself, join our community slack and champion us with a GitHub star ⭐.
The opportunity to be a part of the exciting early stages of a well-funded, European-based Open Source start-up that has massive growth and venture potential
Fully Remote Working Environment
23+ Days of Planned Leave Annually
Paid sick leave and private healthcare plan
We support paid parental leave
Home office, work and well-being allowances (for yoga, gym etc.) and other nice benefits
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