MMLSpark on Adult Census

By for September 13, 2017

Report Abuse
This sample demonstrates the power of simplification by implementing a binary classfier using the popular Adult Census dataset, first with mmlspark library then comparing that with the standad Spark ML constructs.
# Using MMLSpark to Classify Income Level This sample demonstrates the power of simplification by implementing a binary classfier using the popular Adult Census dataset, first with mmlspark library then comparing that with the standad Spark ML constructs. To learn more about mmlspark library, please visit: http://github.com/azure/mmlspark. Run train_mmlspark.py in a local Docker container. ``` $ az ml experiment submit -c docker train_mmlspark.py 0.1 ``` Create myvm.compute file to point to a remove VM ``` $ az ml computetarget attach --name <myvm> --address <ip address or FQDN> --username <username> --password <pwd> ``` Run train_mmlspark.py in a Docker container (with Spark) in a remote VM: ``` $ az ml experiment submit -c myvm train_mmlspark.py 0.3 ``` Create myhdi.compute to point to an HDI cluster ``` $ az ml computetarget attach --name <myhdi> --address <ip address or FQDN of the head node> --username <username> --password <pwd> --cluster ``` Run it in a remote HDInsight cluster: ``` $ az ml experiment submit -c myhdi train_mmlspark.py 0.5 ```