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Deep learning
Keras Neural network Image classification LSTM Sequence analysis
+10
  1. Workflow
    Sentiment Analysis with BERT
    Deep Learning NLP Machine Learning
    +8
    This workflow demonstrates how to do sentiment analysis by fine-tuning Google's BERT network. The idea is straight forward: A sma…
    knime > Examples > 04_Analytics > 14_Deep_Learning > 04_TensorFlow2 > 01_BERT_Sentiment_Analysis
    12
  2. Workflow
    Multivariate Time Series Analysis with an RNN - Training
    Time series Deep learning RNN
    +3
    This is a simple example workflow for multivariant time series analysis using an LSTM based recurrent neural network and implemen…
    kathrin > Multivariate Times Series with RNN > Multivariate_Time_Series_RNN_Keras_Training
    4
  3. Workflow
    Simple CNN for Image Classification
    Deep learning Keras Image classification
    This workflow trains a simple convolutional neural network (CNN) on the MNIST dataset using Keras. The enclosed pictures are from…
    kathrin > Codeless Deep Learning with KNIME > Chapter 9 > MNIST_Classification > Image_Classification_MNIST
    3
  4. 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
  5. Workflow
    01_Train GAN for Image Generation
    Deep learning GAN Image generation
    There has been no description set for this workflow's metadata.
    emilio_s > Blogposts > GANs for Image Generation > 01_Train GAN for Image Generation
    2
  6. Workflow
    Multivariate Time Series Analysis with an RNN - Deployment
    Time series Deep learning RNN
    +3
    This is a simple example workflow for the deployment of a multivariant time series, LSTM based, recurrent neural network. It is b…
    kathrin > Multivariate Times Series with RNN > Multivariate_Time_Series_RNN_Keras_Deployment
    2
  7. 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
  8. 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
  9. Workflow
    Mixing Deep Learning with XGBoost
    Deep Learning Machine Learning XGBoost
    +11
    This workflow shows how to train an XGBoost based image classifier that uses a pretrained convolutional neural network to extract…
    christian.birkhold > My Sandbox > Mixing_DL_with_XGBoost
    1
  10. Workflow
    Tic-Tac-Toe Learn
    Keras Reinforcment Learning Game
    +2
    Training a Reinforcment Learning Model to play Tic-Tac-Toe with the Keras Deep Learning Integration.
    corey > Public > Tic-Tac-Toe > Tic-Tac-Toe Learn
    1
  11. Workflow
    Tic-Tac-Toe Play
    Reinforcment Learning Keras Deep Learning
    +2
    A workflow deploying the network trained in the Tic-Tac-Toe Learn workflow to a KNIME Webportal application to enable interactive…
    corey > Public > Tic-Tac-Toe > Tic-Tac-Toe Play
    1
  12. Workflow
    Preprocess image data
    Deep learning Keras Image classification
    In this workflow we pre-process the image data, which we will use throughout the following example workflows. Please note: The wo…
    knime > Examples > 04_Analytics > 14_Deep_Learning > 02_Keras > 04_Cats_and_Dogs > 01_Preprocess_image_data
    1
  13. 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
  14. 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
  15. Workflow
    [KNIME Nodes] KN-301 Simple Demand Forecasting Neural Networks
    Neural Networks Deep Learning Sales Forecast
    Compares the Keras Layer Nodes against the DL Python nodes. Builds four models which attempt to predict future sales. Two models …
    scientificstrategy > Public > KNIME Nodes > KN-301 Simple Demand Forecasting Neural Networks v05
    1
  16. 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
    1
  17. Workflow
    KNIME Deep Learning - Train MNIST classifier with Keras nodes
    Deep learning Keras Image classification
    This workflow trains a simple convolutional neural network (CNN) on the MNIST dataset via Keras. You can use either a code based …
    scottf > Public > Train_MNIST_classifier_Keras_Nodes
    1
  18. 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
  19. 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
  20. 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