Predicting the number of bicycles at rental stations.

Testing out NannyML

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

A repo to detect drift in data using Alibi Detect

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

Python library for monitoring machine learning models, detecting data drift and overfitting to ensure robust and reliable performance.

Drift Lens Demo

Repository showcasing my Machine Learning Engineering Apprenticeship at AXA-Direct Assurance, contributing to the development and implementation of Machine Learning solutions.

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.

A system for monitoring statistical data distribution shifts in distributed settings

"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.

Drift-Lens: an Unsupervised Drift Detection Framework for Deep Learning Classifiers on Unstructured Data

A tiny framework to perform adversarial validation of your training and test data.

The Unstable Population Indicator

Data Drift Analysis and Anomaly detection tools

Adversarial labeller is a sklearn compatible instance labelling tool for model selection under data drift.

End to End Machine Learning Observability Project

Dataset shift with outlier scores

Passively collect images for computer vision datasets on the edge.