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:
mlflow.pyspark.ml.autolog()API for autologging of
pyspark.mlestimators (#4228, @WeichenXu123)
mlflow.catboost.load_modelAPIs for CatBoost model persistence (#2417, @harupy)
mlflow.pyfunc.spark_udfto use column names from model signature by default (#4236, @Loquats)
datetimedata type for model signatures (#4241, @vperiyasamy)
mlflow.sklearn.eval_and_log_metricsAPI that computes and logs metrics for the given scikit-learn model and labeled dataset. (#4218, @alkispoly-db)