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  • 07_Sentiment_Analysis_with_Deep_Learning
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Sentiment Analysis

deep learning keras text classification classification lstm +10

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This workflow shows how to train a simple neural network for text classification, in this case sentiment analysis. The used network learns a 128 dimensional word embedding followed by an LSTM. This example is adapted from the following Keras example script: https://github.com/keras-team/keras/blob/master/examples/imdb_lstm.py In order to run the example, please make sure you have the following KNIME extensions installed: * KNIME Deep Learning - Keras Integration (Labs) You also need a local Python installation that includes Keras. Please refer to https://www.knime.com/deeplearning#keras for installation recommendations and further information.

External resources

  • Keras example script

Used extensions & nodes

Created with KNIME Analytics Platform version 4.1.0
  • KNIME Core Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.0

  • KNIME Deep Learning - Keras Integration Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.0

  • KNIME JavaScript Views Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.0

  • KNIME Python Integration Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.0

  • KNIME Quick Forms Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.0

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License (CC-BY-4.0)
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