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Neural network
Deep learning Credit Rating Credit Scoring Customer Risk Decision Tree SVM Keras Sequence analysis
  1. Go to item
    Workflow
    Sentiment Analysis
    Deep learning Keras Text classification
    +9
    This workflow shows how to train a simple neural network for text classification, in this case sentiment analysis. The used netwo…
    andisa.dewi > Public > Deep Learning Workshop > Sentiment_Analysis_Deep_Learning
    3
    andisa.dewi
  2. Go to item
    Workflow
    Sentiment Analysis
    Deep learning Keras Text classification
    +11
    This workflow shows how to train a simple neural network for text classification, in this case sentiment analysis. The used netwo…
    knime > Examples > 04_Analytics > 14_Deep_Learning > 02_Keras > 08_Sentiment_Analysis_with_Deep_Learning_KNIME_nodes
    3
    knime
  3. Go to item
    Workflow
    Credit Scoring
    Credit Scoring Credit Rating Customer Risk
    +3
    This KNIME workflow focuses on creating a credit scoring model based on historical data. As with all data mining modeling activit…
    maitri > Public > credit scoring 0208
    2
    maitri
  4. Go to item
    Workflow
    Credit Scoring
    Credit Scoring Credit Rating Customer Risk
    +3
    This KNIME workflow focuses on creating a credit scoring model based on historical data. As with all data mining modeling activit…
    diksha_kri07 > Public > Credit Scoring Model(diksha kumari)
    2
    diksha_kri07
  5. Go to item
    Workflow
    Distances on Word Embeddings
    Word embedding Word2Vec Neural network
    +3
    Here we use word embedding instead of hot encoding, using a Word2Vec Learner node. The hidden layer size is set to 10, therefore …
    knime > Examples > 08_Other_Analytics_Types > 01_Text_Processing > 21_Word_Embedding_Distance
    2
    knime
  6. Go to item
    Workflow
    Credit Scoring
    Credit Scoring Credit Rating Customer Risk
    +3
    This KNIME workflow focuses on creating a credit scoring model based on historical data. As with all data mining modeling activit…
    gunjan_710 > Public > Building a Credit Scoring Model
    1
    gunjan_710
  7. 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
  8. Go to item
    Workflow
    Keras Autoencoder for Fraud Detection - Deployment
    Autoencoder Keras Neural network
    +15
    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
    1
    kathrin
  9. Go to item
    Workflow
    Keras Autoencoder for Fraud Detection - Training
    Autoencoder Keras Neural network
    +12
    This workflow trains an autoendcoder model to detect fraudulent transactions.
    kathrin > Codeless Deep Learning with KNIME > Chapter 5 > 01_Autoencoder_for_Fraud_Detection_Training
    1
    kathrin
  10. Go to item
    Workflow
    ECG Heartbeat Classification Dataset (PTB)
    ECG Conv1D Neural Network
    +4
    This ECG dataset is provided by Physikalisch-Technische Bundesanstalt (PTB) and is available on Kaggle (https://www.kaggle.com/sh…
    knime > Digital Healthcare > ECG Arrythmia Detection > ecg_cnn_ptb
    1
    knime
  11. Go to item
    Workflow
    ECG MIT-BIH Data Analysis and Modelling
    ECG Arrhythmia CNN
    +6
    This is also the ECG dataset from Kaggle, put together from PhysioNet MIT-BIH Arrhythmia (https://www.kaggle.com/shayanfazeli/hea…
    knime > Digital Healthcare > ECG Arrythmia Detection > ecg_cnn_mit
    1
    knime
  12. Go to item
    Workflow
    Credit Scoring
    Credit Scoring Credit Rating Customer Risk
    +5
    This workflow creates a credit scoring model based on historical data. As with all data mining modeling activities, it is unclear…
    anamika10 > Public > 01_CreditScoring
    1
    anamika10
  13. Go to item
    Workflow
    Energy Demand Prediction with LSTM - Deployment
    Time Series Prediction Energy Usage
    +4
    This workflow applies an LSTM network to predict energy demand using lagged values of a time series as input.
    kathrin > Codeless Deep Learning with KNIME > Chapter 6 > 02_TSA_with_LSTM_Network_Deployment
    1
    kathrin
  14. Go to item
    Workflow
    Energy Demand Prediction with LSTM - Training
    Time Series Prediction Energy Usage
    +4
    This workflow trains and applies an LSTM network to predict energy demand using lagged values of a time series as input. In the E…
    kathrin > Codeless Deep Learning with KNIME > Chapter 6 > 01_TSA_with_LSTM_Network_Training
    1
    kathrin
  15. Go to item
    Workflow
    U-Net Encoder Decoder Architecture for Cell Segmentation
    Cell segmentation Cell image Neural network
    +4
    This workflow creates and trains a Unet for segmenting cell images. The trained network is used to predict the segmentation of un…
    janina > Public > UNet_Keras_CellSegmentation
    1
    janina
  16. Go to item
    Workflow
    Sentiment Analysis
    Deep learning Keras Text classification
    +9
    This workflow shows how to train a simple neural network for text classification, in this case sentiment analysis. The used netwo…
    scottf > Public > TextMiningWebinar > Sentiment > Sentiment_Deep_Learning
    1
    scottf
  17. Go to item
    Workflow
    Generate predictions with ONNX
    Machine learning PyTorch ChEMBL
    +3
    This workfow uses a multitask neural network built using PyTorch and saved to the ONNX format to generate predictions. The networ…
    knime > Life Sciences > Cheminformatics > ONNX > Generate ChEMBL Predictions
    1
    knime
  18. Go to item
    Workflow
    Keras Autoencoder for Fraud Detection Training
    Autoencoder Keras Neural network
    +16
    Partition numeric input data into a training, test, and validation set. Normalize the data into range [0,1]. Build a Keras autoen…
    knime > Examples > 50_Applications > 39_Fraud_Detection > 03_Keras_Autoencoder_for_Fraud_Detection_Training
    1
    knime
  19. Go to item
    Workflow
    Keras Autoencoder for Fraud Detection Deployment
    Autoencoder Keras Neural network
    +16
    Read Keras model. Read deployment data, which are normalized into range [0,1]. Apply the Keras model to the deployment data, calc…
    knime > Examples > 50_Applications > 39_Fraud_Detection > 04_Keras_Autoencoder_for_Fraud_Detection_Deployment
    1
    knime
  20. Go to item
    Workflow
    Neural Machine Translation from English to German: Training Workflow
    Deep learning Keras Sequence analysis
    +12
    Uses a character level encoder-decoder network of LSTMs. The encoder network reads the input sentence character by character and …
    knime > Examples > 04_Analytics > 14_Deep_Learning > 02_Keras > 12_Machine_Translation > 01_Training_a_Neural_Machine_Translation_Model
    1
    knime

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