Agent skill · research science · datadrivenconstruction
ml-model-retrainer
Automated pipeline for retraining ML models with new construction data. Monitor model drift, trigger retraining, and validate model performance.
Why this skill is useful
Adds a complete automated pipeline for retraining ML models specific to construction data, including monitoring for model drift and validation processes.
What it needs
Requires python3 installed locally. About 5k tokens when loaded. Last updated 2026-02-14. 265 stars on the source repository.
What this skill does
ML Model Retrainer for Construction Overview Automated pipeline for keeping construction ML models up-to-date. Monitor for data drift, trigger retraining when needed, validate performance, and manage model versions. Business Case ML models degrade over time as: Market conditions change (material prices, labor rates) New construction methods emerge Project complexity evolves Regional factors shift Continuous retraining ensures predictions remain accurate. Technical Implementation Quick Start Dependencies
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills datadrivenconstruction/ml-model-retrainer