MLflow 0.8.1 Released

Aaron Davidson, et al, announce a new version of Databricks MLflow:

When scoring Python models as Apache Spark UDFs, users can now filter UDF outputs by selecting from an expanded set of result types. For example, specifying a result type of pyspark.sql.types.DoubleType filters the UDF output and returns the first column that contains double precision scalar values. Specifying a result type of pyspark.sql.types.ArrayType(DoubleType) returns all columns that contain double precision scalar values. The example code below demonstrates result type selection using the result_type parameter. And the short example notebook illustrates Spark Model logged and then loaded as a Spark UDF.

Read on for a pretty long list of updates.

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