We are happy to announce the availability of MLflow 1.4.0!

In addition to bug and documentation fixes, MLflow 1.4.0 includes the following major features and improvements:

  • Model Registry (Beta). MLflow 1.4.0 adds an experimental model registry feature, where you can manage, version, and keep lineage of your production models.
  • TensorFlow updates
    • MLflow Keras model saving, loading, and logging has been updated to be compatible with TensorFlow 2.0.
    • Autologging for tf.estimator and tf.keras models has been updated to be compatible with TensorFlow 2.0. The same functionalities of autologging in TensorFlow 1.x are available in TensorFlow 2.0, namely when fitting tf.keras models and when exporting saved tf.estimator models.
    • Examples and READMEs for both TensorFlow 1.X and TensorFlow 2.0 have been added to mlflow/examples/tensorflow.

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