Sourced from mlflow's releases.

MLflow 1.17.0 includes the following major features and improvements:

Features:

• Add support for hyperparameter-tuning models to mlflow.pyspark.ml.autolog() (#4270, @​WeichenXu123)

Bug fixes and documentation updates:

• Fix PyTorch Lightning callback definition for compatibility with PyTorch Lightning 1.3.0 (#4333, @​dbczumar)
• Fix a bug in scikit-learn autologging that omitted artifacts for unsupervised models (#4325, @​dbczumar)
• Support logging datetime.date objects as part of model input examples (#4313, @​vperiyasamy)
• Implement HTTP request retries in the MLflow Java client for 500-level responses (#4311, @​dbczumar)
• Include a community code of conduct (#4310, @​dennyglee)

Small bug fixes and doc updates (#4276, #4263, @​WeichenXu123; #4289, #4302, #3599, #4287, #4284, #4265, #4266, #4275, #4268, @​harupy; #4335, #4297, @​dbczumar; #4324, #4320, @​tleyden)

MLflow 1.16.0 includes several major features and improvements:

Features:

• 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)

Bug fixes and documentation updates:

• Fix a database migration error for PostgreSQL (#4211, @​dolfinus)
• Fix autologging silent mode bugs (#4231, @​dbczumar)

Small bug fixes and doc updates (#4255, #4252, #4254, #4253, #4242, #4247, #4243, #4237, #4233, @​harupy; #4225, @​dmatrix; #4206, @​mlflow-automation; #4207, @​shrinath-suresh; #4264, @​WeichenXu123; #3884, #3866, #3885, @​ankan94; #4274, #4216, @​dbczumar)

MLflow 1.15.0

1.15.0 (2021-03-26)

MLflow 1.15.0 includes several features, bug fixes and improvements. Notably, it includes a number of improvements to MLflow autologging:

Features:

• Add silent=False option to all autologging APIs, to allow suppressing MLflow warnings and logging statements during autologging setup and training (#4173, @​dbczumar)
• Add disable_for_unsupported_versions=False option to all autologging APIs, to disable autologging for versions of ML frameworks that have not been explicitly tested against the current version of the MLflow client (#4119, @​WeichenXu123)

Bug fixes:

• Autologged runs are now terminated when execution is interrupted via SIGINT (#4200, @​dbczumar)
• The R mlflow_get_experiment API now returns the same tag structure as mlflow_list_experiments and mlflow_get_run (#4017, @​lorenzwalthert)
• Fix bug where mlflow.tensorflow.autolog would previously mutate the user-specified callbacks list when fitting tf.keras models (#4195, @​dbczumar)
• Fix bug where SQL-backed MLflow tracking server initialization failed when using the MLflow skinny client (#4161, @​eedeleon)
• Model version creation (e.g. via mlflow.register_model) now fails if the model version status is not READY (#4114, @​ankit-db)

... (truncated)

Sourced from mlflow's changelog.

1.17.0 (2021-05-07)

MLflow 1.17.0 includes several major features and improvements:

Features:

• Add support for hyperparameter-tuning models to mlflow.pyspark.ml.autolog() (#4270, @​WeichenXu123)

Bug fixes and documentation updates:

• Fix PyTorch Lightning callback definition for compatibility with PyTorch Lightning 1.3.0 (#4333, @​dbczumar)
• Fix a bug in scikit-learn autologging that omitted artifacts for unsupervised models (#4325, @​dbczumar)
• Support logging datetime.date objects as part of model input examples (#4313, @​vperiyasamy)
• Implement HTTP request retries in the MLflow Java client for 500-level responses (#4311, @​dbczumar)
• Include a community code of conduct (#4310, @​dennyglee)

Small bug fixes and doc updates (#4276, #4263, @​WeichenXu123; #4289, #4302, #3599, #4287, #4284, #4265, #4266, #4275, #4268, @​harupy; #4335, #4297, @​dbczumar; #4324, #4320, @​tleyden)

1.16.0 (2021-04-22)

MLflow 1.16.0 includes several major features and improvements:

Features:

• 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)

Bug fixes and documentation updates:

• Fix a database migration error for PostgreSQL (#4211, @​dolfinus)
• Fix autologging silent mode bugs (#4231, @​dbczumar)

Small bug fixes and doc updates (#4255, #4252, #4254, #4253, #4242, #4247, #4243, #4237, #4233, @​harupy; #4225, @​dmatrix; #4206, @​mlflow-automation; #4207, @​shrinath-suresh; #4264, @​WeichenXu123; #3884, #3866, #3885, @​ankan94; #4274, #4216, @​dbczumar)

1.15.0 (2021-03-26)

MLflow 1.15.0 includes several features, bug fixes and improvements. Notably, it includes a number of improvements to MLflow autologging:

Features:

• Add silent=False option to all autologging APIs, to allow suppressing MLflow warnings and logging statements during autologging setup and training (#4173, @​dbczumar)
• Add disable_for_unsupported_versions=False option to all autologging APIs, to disable autologging for versions of ML frameworks that have not been explicitly tested against the current version of the MLflow client (#4119, @​WeichenXu123)

Bug fixes:

• Autologged runs are now terminated when execution is interrupted via SIGINT (#4200, @​dbczumar)
• The R mlflow_get_experiment API now returns the same tag structure as mlflow_list_experiments and mlflow_get_run (#4017, @​lorenzwalthert)

... (truncated)

• 8632218 Merge remote-tracking branch 'weichen/test_publish' into branch-1.17
• 1a54a39 Update versions (#4335)
• ab6dc11 Fix PyTorch Lightning callback hook args (#4333)
• 712c9c7 Update MLflow version to 1.17.0 (#4334)
• 776ce84 Sklearn autologging bug fix: Don't compute metrics when labels are missing (#...
• 0f50872 Document brew dependencies for OSX, split pip install into two sections (#4324)
• 29291bd Change "source activate" -> "conda activate" (#4320)
• 0248adc Implementation: autologging for hyperparameter-tuning (#4270)
• 2829e04 Make datetime.date objects JSON serializable (#4313)
• af54bbd MLflow Java client: Retry on 500s (#4311)
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