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01_​Model_​Monitoring_​with_​AutoML_​and_​MLOps

Model Monitoring with Integrated Deployment
load a simpleML Modelnew training setpast deployment datatraining setextracting past deployment data for new training set( up to 2009-05-31 )deploy ML model(if it was not already)re-deploy ML modelre-trainML modelRight Click > Execute & Open Viewtop: Currently Deployed Modelbottom: Deployment DataRight Click > Execute & Open Viewtop: Currently Deployed Modelmiddle : New Modelbottom : Deployment DataAutoML Concatenate Table Reader Table Reader Date&Time-basedRow Filter KNIME ServerConnector Deploy Workflowto Server Deploy Workflowto Server AutoML Model Monitor View Model MonitorView (Compare) load a simpleML Modelnew training setpast deployment datatraining setextracting past deployment data for new training set( up to 2009-05-31 )deploy ML model(if it was not already)re-deploy ML modelre-trainML modelRight Click > Execute & Open Viewtop: Currently Deployed Modelbottom: Deployment DataRight Click > Execute & Open Viewtop: Currently Deployed Modelmiddle : New Modelbottom : Deployment DataAutoML Concatenate Table Reader Table Reader Date&Time-basedRow Filter KNIME ServerConnector Deploy Workflowto Server Deploy Workflowto Server AutoML Model Monitor View Model MonitorView (Compare)

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To use this workflow in KNIME, download it from the below URL and open it in KNIME:

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Created by: corey
Created at: 2020-09-29
On NodePit since: 2021-01-19
Last update: 2024-04-18
Created with KNIME version: v4.3.0
Tags: model managementmodel monitoringmonitormodel governanceMLOpsintegrated deploymentAIOpsModelOpsDataOps

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