Day: February 20, 2019

Execute Machine Learning Jobs in Microsoft Azure Databricks from StreamSets

In my previous blog post, I demonstrated how to achieve low-latency inference using Databricks ML models in StreamSets. Now let’s say you have a dataflow pipeline that is ingesting data, enriching it, performing transformations, and based on certain condition(s), you’d like to (re)train the Databricks ML model. For instance, using different value for hyperparameter n_estimators […]

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