Information Hub

MLflow experiment tracking tutorial after work: params, metrics, artifacts

After-work guide to mlflow experiment tracking tutorial: log params/metrics so tonight's run is findable tomorrow. Educational only. Not investment advice.

pythonmlflowsecuritymlopsafter-work

GHSA-gqvg-gmmx-x4hm after work: harden MLflow statsmodels loads (defense only)

GHSA-gqvg-gmmx-x4hm: mlflow.statsmodels ignored MLFLOW_ALLOW_PICKLE_DESERIALIZATION before 3.15.0 — crafted artifacts via load_model could RCE even when env=False. Defense: upgrade ≥3.15 (prefer 3.16+), no untrusted artifacts, restrict store writes. Not investment advice.

pythondartsmlflowforecastingafter-work

Darts 0.47.0 after work: official MLflow for forecasting experiments

Darts 0.47.0 (~2026-09-06): official MLflow integration to track/compare/persist forecasting experiments; see MLflow quickstart notebook. Not bundled with Prophet/Chronos/TimesFM/sktime posts. Not investment advice.