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Anomaly detection
Education
Fraud detection Keras Autoencoder Decoder Deep learning Encoder Neural network Reconstruction
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    Workflow
    Keras Autoencoder for Fraud Detection - Deployment
    Autoencoder Keras Neural network
    +16
    Exercise of the L4-DL Introduction to Deep Learning Course. The goal of this exercise is to apply a trained autoencoder to new tr…
    knime > Education > Courses > L4-DL Introduction to Deep Learning > Session2 > Exercises > 02_Fraud_Detection_Deployment_Exercise
    0
    knime
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    Workflow
    Keras Autoencoder for Fraud Detection - Deployment
    Autoencoder Keras Neural network
    +16
    Exercise of the L4-DL Introduction to Deep Learning Course. The goal of this exercise is to apply a trained autoencoder to new tr…
    knime > Education > Courses > L4-DL Introduction to Deep Learning > Session2 > Solutions > 02_Fraud_Detection_Deployment_Solution
    0
    knime
  3. Go to item
    Workflow
    Keras Autoencoder for Fraud Detection - Training
    Autoencoder Keras Neural network
    +13
    Exercise of the L4-DL Introduction to Deep Learning Course. The goal of this exercise is to train an autoencoder model to detect …
    knime > Education > Courses > L4-DL Introduction to Deep Learning > Session2 > Exercises > 01_Fraud_Detection_Training_Exercise
    0
    knime
  4. Go to item
    Workflow
    Keras Autoencoder for Fraud Detection - Training
    Autoencoder Keras Neural network
    +13
    Exercise of the L4-DL Introduction to Deep Learning Course. The goal of this exercise is to train an autoencoder model to detect …
    knime > Education > Courses > L4-DL Introduction to Deep Learning > Session2 > Solutions > 01_Fraud_Detection_Training_Solution
    0
    knime
  5. Go to item
    Workflow
    Keras Autoencoder for Fraud Detection - Integrated Deployment
    Autoencoder Keras Neural network
    +13
    This workflow replicates the exercises of session 2, combining training and deployment using Integrated deployment. The purple bo…
    knime > Education > Courses > L4-DL Introduction to Deep Learning > Supplementary workflows > Autoencoder > 01_Fraud_Detection_Integrated_Deployment
    0
    knime
  6. Go to item
    Workflow
    Keras Autoencoder for Fraud Detection - Integrated Deployment Call
    Autoencoder Keras Neural network
    +16
    This workflow executes the model generated by the Integrated deployment to get a prediction of fraudolent transaction.
    knime > Education > Courses > L4-DL Introduction to Deep Learning > Supplementary workflows > Autoencoder > 02_Fraud_Detection_Call
    0
    knime
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    Workflow
    Anomaly Detection (Exercise)
    Fraud detection Anomaly detection Text processing
    +5
    This workflow instructs you to detect anomalies in contracts via the IQR, z-score, and isolation forest techniques. Furthermore, …
    knime > Education > Courses > L4-DV Low Code Data Extraction and Visualization > Session_4 > 01_Exercises > 04_Anomaly_Detection_Exercise
    0
    knime
  8. Go to item
    Workflow
    Anomaly Detection (Exercise) - Solution
    Fraud detection Anomaly detection Text processing
    +5
    This workflow instructs you to detect anomalies in contracts via the IQR, z-score, and isolation forest techniques. Furthermore, …
    knime > Education > Courses > L4-DV Low Code Data Extraction and Visualization > Session_4 > 02_Solutions > 04_Anomaly_Detection_Solution
    0
    knime
  9. Go to item
    Workflow
    Anomaly Detection (Exercise)
    Fraud detection Anomaly detection Text processing
    +5
    This workflow instructs you to detect anomalies in contracts via the IQR, z-score, and isolation forest techniques. Furthermore, …
    hayasaka > KNIME Fall Summit Training 2022 > L4-DV Low Code Data Extraction and Visualization > Session_4 > 01_Exercises > 04_Anomaly_Detection_Exercise
    0
    hayasaka
  10. Go to item
    Workflow
    Anomaly Detection (Exercise)
    Fraud detection Anomaly detection Text processing
    +5
    This workflow instructs you to detect anomalies in contracts via the IQR, z-score, and isolation forest techniques. Furthermore, …
    chemgirl36 > Public Space > L4-DV Low Code Data Extraction and Visualization > Session_4 > 01_Exercises > 04_Anomaly_Detection_Exercise
    0
    chemgirl36
  11. Go to item
    Workflow
    Anomaly Detection (Exercise) - Solution
    Fraud detection Anomaly detection Text processing
    +5
    This workflow instructs you to detect anomalies in contracts via the IQR, z-score, and isolation forest techniques. Furthermore, …
    hayasaka > KNIME Fall Summit Training 2022 > L4-DV Low Code Data Extraction and Visualization > Session_4 > 02_Solutions > 04_Anomaly_Detection_Solution
    0
    hayasaka
  12. Go to item
    Workflow
    Anomaly Detection (Exercise) - Solution
    Fraud detection Anomaly detection Text processing
    +5
    This workflow instructs you to detect anomalies in contracts via the IQR, z-score, and isolation forest techniques. Furthermore, …
    chemgirl36 > Public Space > L4-DV Low Code Data Extraction and Visualization > Session_4 > 02_Solutions > 04_Anomaly_Detection_Solution
    0
    chemgirl36
  13. Go to item
    Workflow
    Autoencoder MNIST MidPoint Focus
    Autoencoder Keras Neural network
    +8
    Exploring the latent space of an autoencoder for dimensional reduction
    iceman > Public > Autoencoder MNIST MidPoint Focus
    1
    iceman

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