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, and interactive visualizations, is completely model-agnostic, and currently supports all tabular classification use cases. NannyML closes the loop with performance monitoring and post deployment data science, empowering data scientist to quickly understand and automatically detect silent model failure. By using NannyML, data scientists can finally maintain complete visibility and trust in their deployed machine learning models. When the actual outcome of your deployed prediction models is delayed, or even when post-deployment target labels are completely absent, you can use NannyML's CBPE-algorithm to estimate model performance.

Features

  • Performance estimation and monitoring
  • End sleepless nights caused by not knowing your model performance
  • Analyse data drift and model performance over time
  • Discover the root cause to why your models are not performing as expected
  • No alert fatigue! React only when necessary if model performance is impacted
  • Painless setup in any environment

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License

Apache License V2.0

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Additional Project Details

Programming Language

Python

Related Categories

Python Machine Learning Software, Python Data Science Tool

Registered

2022-08-22