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02_​Basic_​Learner_​View_​Tutorial

Workflow

How to use the Learner View

This workflow shows an example of the View of the DL4J Feedforward Leaner nodes.

deeplearning machine learning neural networks view
How to use the Learner ViewThis workflow shows an example of the View shared by all DL4J Feedforward Learner nodes. During execution, the currentlearning status as well as the current error can be viewed in the Learner Node View. Additionally, the bottom of the viewshows a history of the error of the network after each epoch. The view updates automatically after each adjustment of thenetwork parameters. The view can be opened by Right Click > View: Learning Status. Additionally, the learning can bestopped manually by clicking the 'Stop Learning' button in the Learner Node View. This will stop learning after the currentbatch and save the model in the current status. This is especially useful if the error doesn't significantly decrease anymoreduring learning so we can stop the learning process without having to wait for all epochs to be finished. Note that after the'Stop Learning Button' was clicked the model will be directly ready to use.Workflow RequirementsKNIME Analytics Platform 3.4.0KNIME Deeplearning4J Integration This metanode creates a simple general purpose multi layer perceptron consisting oftwo fully connected (FC) layers. Parameters for all layers:Learning Rate: 0.01Activation Function: ReLU Right Click > View: Learning Status100 FCUnits100 FCUnitsData Generator DL4J Feedforward Learner(Classification) Dense Layer DL4J ModelInitializer Dense Layer How to use the Learner ViewThis workflow shows an example of the View shared by all DL4J Feedforward Learner nodes. During execution, the currentlearning status as well as the current error can be viewed in the Learner Node View. Additionally, the bottom of the viewshows a history of the error of the network after each epoch. The view updates automatically after each adjustment of thenetwork parameters. The view can be opened by Right Click > View: Learning Status. Additionally, the learning can bestopped manually by clicking the 'Stop Learning' button in the Learner Node View. This will stop learning after the currentbatch and save the model in the current status. This is especially useful if the error doesn't significantly decrease anymoreduring learning so we can stop the learning process without having to wait for all epochs to be finished. Note that after the'Stop Learning Button' was clicked the model will be directly ready to use.Workflow RequirementsKNIME Analytics Platform 3.4.0KNIME Deeplearning4J Integration This metanode creates a simple general purpose multi layer perceptron consisting oftwo fully connected (FC) layers. Parameters for all layers:Learning Rate: 0.01Activation Function: ReLU Right Click > View: Learning Status100 FCUnits100 FCUnitsData Generator DL4J Feedforward Learner(Classification) Dense Layer DL4J ModelInitializer Dense Layer

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Resources

Nodes

02_​Basic_​Learner_​View_​Tutorial consists of the following 5 nodes(s):

Plugins

02_​Basic_​Learner_​View_​Tutorial contains nodes provided by the following 2 plugin(s):