ml-model-retrainer
datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction ↗
From the author
Automated pipeline for retraining ML models with new construction data. Monitor model drift, trigger retraining, and validate model performance.
Install
npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill ml-model-retrainer -a claude-code
Installs to .claude/skills/ml-model-retrainer/ · Each command fetches the skill straight from GitHub with the open skills CLI.
Byte-identical to the scanned commit, with the repository’s licence and a SOURCE.txt.
Want your agent to suggest skills while you type? See how to use skills from your IDE.
Safety checks on SKILL.md
No warnings.
Why 86
aiqbench computes the trust score from public signals. It is not a security audit, so read a skill before you install it.
Similar skills
Closest to this one by what they do and when they are used.
- ml-model-builderdatadrivenconstruction/DDC_Skills_for_AI_Agents_in_ConstructionBuild ML models for construction predictions. Train and evaluate custom models for cost, duration, and risk prediction.Other★ 368
- preprocessing-data-with-automated-pipelinesforyourhealth111-pixel/Vibe-SkillsDesign and implement repeatable preprocessing pipelines for cleaning, encoding, transforming, and validating ML input data.Design★ 3.8K
- ml-pipeline-workflowwshobson/agentsBuild end-to-end MLOps pipelines from data preparation through model training, validation, and production deployment. Use when creating ML pipelines, implementing MLOps practices, or automating model training and deployment workflows.Productivity★ 41.6K
- evaluating-machine-learning-modelsforyourhealth111-pixel/Vibe-SkillsEvaluate trained machine learning models with the right metrics and comparison logic. Use for benchmark review, threshold selection, calibration, validation, and model comparison; not for feature engineering or leakage auditing.Engineering★ 3.8K
- explaining-machine-learning-modelsforyourhealth111-pixel/Vibe-SkillsExplain trained machine learning models through feature attribution, local explanations, and behavior summaries. Use as an explicit/manual helper once a model already exists, not for training ownership, leakage auditing, or general ML strategy selection.Productivity★ 3.8K
- ml-pipelineJeffallan/claude-skillsDesigns and implements production-grade ML pipeline infrastructure: configures experiment tracking with MLflow or Weights & Biases, creates Kubeflow or Airflow DAGs for training orchestration, builds feature store schemas with Feast, deploys model registries, and automates retraining and validation workflows. Use when building ML pipelines, orchestrating training workflows, automating model lifecycle, implementing feature stores, managing experiment tracking systems, setting up DVC for data versioning, tuning hyperparameters, or configuring MLOps tooling like Kubeflow, Airflow, MLflow, or Prefect.DevOps★ 12K
Ratings & reviews
—
no reviews
Tried this skill? Rate it to help others. Sign in
Discussion
Join the discussion. Sign in