- Type: Keras Deep Learning NetworkKeras NetworkThe Keras deep learning network.
- Type: TableData TableThe input table.
Node / Predictor
Keras Network Executor
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- Type: TableData TableThe output table.
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Keras Autoencoder for Fraud Detection Deployment
Read Keras model. Read deployment data, which are normalized into range [0,1]. Apply the …knime > Examples > 50_Applications > 39_Fraud_Detection > 04_Keras_Autoencoder_for_Fraud_Detection_Deployment - Go to item
Keras Autoencoder for Fraud Detection - Deployment
This workflow applies a trained autoencoder model to detect fraudulent transactions.kathrin > Codeless Deep Learning with KNIME > Chapter 5 > 02_Autoencoder_for_Fraud_Detection_Deployment - Go to item
Read Images and Train VGG
This workflow reads image patches downloaded and prepared by the previous workflows in th…knime > Examples > 50_Applications > 31_Histopathology_Blog_Post > _legacy_version > 02_Read_Images_and_Train_VGG - Go to item
Read Images and Train VGG
This workflow reads image patches downloaded and prepared by the previous workflows in th…b_eslami > Public > 31_Histopathology_Blog_Post > _legacy_version > 02_Read_Images_and_Train_VGG - Go to item
Simple Example for Multiclass Classification with Keras
This workflow trains a fully connected feedforward neural network with 4-8-3 units per la…kathrin > Codeless Deep Learning with KNIME > Chapter 4 > Basic_Example_Iris_Dataset - Go to item
Classifying the iris dataset with ANN 4-3-1
Exercise of the L4-DL Introduction to Deep Learning Course. The goal is to train a multil…knime > Education > Courses > L4-DL Introduction to Deep Learning > Session1 > Solutions > 01_Iris_Classification_ANN_Solution
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