⚓ Eurybia monitors model drift over time and securizes model deployment with data validation

A curated list of awesome open source tools and commercial products for monitoring data quality, monitoring model performance, and profiling data 🚀

In this repository, we will present techniques to detect covariate drift, and demonstrate how to incorporate your own custom drift detection algorithms and visualizations with SageMaker model monitor.

These are my notes of the Udacity Nanodegree Machine Learning DevOps Engineer.

Simulation, testing and comparison of state of the art Unsupervised Concept Drift Detectors used in a batch Machine Learning scenario.

Learn how to handle model drift and perform test-based model monitoring

資料科學的日常研究議題

"Past performance of machine learning model is no guarantee of future results." We call it "model drift" or "model decay". This repository will introduce various methods for detecting model drift.

An ML monitoring framework, applied to an attrition risk assessment system.

This repository lists one of my projects and findings as part of my Machine Learning DevOps Engineer Nanodegree.