Software Development
MLflow 3
MLflow 3 (open-source, pinned to 3.15) for classic-ML MLOps — logging and registering models, promoting versions across dev/staging/prod, standing up a tracking server, evaluating with gates, and serving. Corrects the MLflow 2-era defaults a model reaches for (artifact_path, registry stages and get_latest_versions, top-level mlflow.evaluate with baseline_model, runs-URI registration, pickle serialization, mlruns file stores, MLServer serving) with the MLflow 3 idioms that replaced them (named LoggedModels, aliases and copy_model_version, models.evaluate plus validate_evaluation_results, skops/torch.export defaults, database backends, the FastAPI scoring server). Use when writing, reviewing, or migrating Python code that touches MLflow tracking, the model registry, evaluation, or serving.
- Publisher / source
- pproenca/dot-skills (found on skills.sh)
- Upstream record
- pproenca/dot-skills
- Version
- Version 3
- Published
- Publication review
- Approved for publication
- Content fingerprint
9010b23623c333cb4390cee74f049e3e123268345734f83b2776f5aac5c445ba