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MLflow 1.16.0

· One min read
MLflow maintainers
MLflow maintainers
MLflow maintainers

We are happy to announce the availability of MLflow 1.16.0!

In addition to bug and documentation fixes, MLflow 1.16.0 includes the following features and improvements:

  • Add mlflow.pyspark.ml.autolog() API for autologging of pyspark.ml estimators (#4228, @WeichenXu123)
  • Add mlflow.catboost.log_model, mlflow.catboost.save_model, mlflow.catboost.load_model APIs for CatBoost model persistence (#2417, @harupy)
  • Enable mlflow.pyfunc.spark_udf to use column names from model signature by default (#4236, @Loquats)
  • Add datetime data type for model signatures (#4241, @vperiyasamy)
  • Add mlflow.sklearn.eval_and_log_metrics API that computes and logs metrics for the given scikit-learn model and labeled dataset. (#4218, @alkispoly-db)

For a comprehensive list of changes, see the release change log, and check out the latest documentation on mlflow.org.