Evaluate and monitor ML models from validation to production. Join our Discord: https://discord.com/invite/xZjKRaNp8b
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Updated
Jul 2, 2024 - Jupyter Notebook
Evaluate and monitor ML models from validation to production. Join our Discord: https://discord.com/invite/xZjKRaNp8b
A comprehensive solution for monitoring your AI models in production
nannyml: post-deployment data science in python
Algorithms for outlier, adversarial and drift detection
Drift-Lens: an Unsupervised Drift Detection Framework for Deep Learning Classifiers on Unstructured Data
Toolkit for evaluating and monitoring AI models in clinical settings
Frouros: an open-source Python library for drift detection in machine learning systems.
Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.
A curated list of awesome open source tools and commercial products for monitoring data quality, monitoring model performance, and profiling data 🚀
⚓ Eurybia monitors model drift over time and securizes model deployment with data validation
Drift Lens Demo
Repository showcasing my Machine Learning Engineering Apprenticeship at AXA-Direct Assurance, contributing to the development and implementation of Machine Learning solutions.
Online and batch-based concept and data drift detection algorithms to monitor and maintain ML performance.
A system for monitoring statistical data distribution shifts in distributed settings
Free Open-source ML observability course for data scientists and ML engineers. Learn how to monitor and debug your ML models in production.
A reusable codebase for fast data science and machine learning experimentation, integrating various open-source tools to support automatic EDA, ML models experimentation and tracking, model inference, model explainability, bias, and data drift analysis.
Curated list of open source tooling for data-centric AI on unstructured data.
Passively collect images for computer vision datasets on the edge.
The Unstable Population Indicator
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