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Neural Network
Deep learning Keras Sequence analysis Text analysis Text processing
+2
  1. 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
  2. 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
    2
  3. 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
  4. 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
  5. 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
  6. 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
  7. 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
  8. Workflow
    ECG MIT-BIH Data Analysis and Modelling
    ECG Arrhythmia CNN
    +5
    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
  9. 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
  10. 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
  11. 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
  12. 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
  13. 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
  14. Workflow
    ECG Heartbeat Classification Dataset (PTB)
    ECG Conv1D Neural Network
    +3
    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
  15. 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
  16. Workflow
    Different options to train an autoencoder using TensorFlow 2
    Autoencoder Keras Neural network
    +5
    This workflow shows the different options of training and executing a network using TF2 on the example of an autoencoder: Option …
    knime > Examples > 04_Analytics > 14_Deep_Learning > 04_TensorFlow2 > 02_Tensorflow2_Autoencoder_for_Fraud_Detection_Training
    1
  17. Workflow
    Cell Segmentation
    Unet Tensorflow2 TF2
    +4
    This workflow uses Tensorflow2 to create and train a Unet for segmenting cell images. The trained network is used to predict the …
    knime > Examples > 04_Analytics > 14_Deep_Learning > 04_TensorFlow2 > 03_Tensorflow2_CellSegmentation
    1
  18. Workflow
    01_Neural_Net
    Neural network Machine learning Deep learning
    This workflow trains a neural network on Statlog (Landsat Satellite) Data Set. Each row represents the pixel values in the four s…
    k10shetty1 > Public > 01_Neural_Net
    0
  19. Workflow
    02_Deployment
    GIDS Exercise Academia
    +4
    In this exercise you will use a previously trained neural network to predict some unseen data.
    knime > Academic Alliance > Guide to Intelligent Data Science > Exercises > Chapter9_Neural_Networks > Exercise > 02_Deployment
    0
  20. 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…
    deepks2014 > Public > Example Workflows > Customer Intelligence > Credit Scoring > Building a Credit Scoring Model
    0