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Keras Embedding Layer

AnalyticsIntegrationsDeep LearningKerasLayers
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An embedding network layer. This layer receives a sequence of non-negative integer indices and learns to embed those into a high dimensional vector (the size of which is specified by output dimension). This layer can only be used as the first layer in a model (after the input layer). Corresponds to the Embedding Keras layer . Note that the Keras documentation is outdated. The input to this layer can be of arbitrary rank and the output of this layer will have to be a tensor with one additional dimension. The inputs to this layer i.e. the values fed in the learner or executor must be integers in the interval [0, n) where n is the specified input dimension.

External resources

  • KNIME Deep Learning Keras Integration

Node details

Input ports
  1. Type: Keras Deep Learning Network
    Keras Network
    The Keras deep learning network to which to add an Embedding layer.
Output ports
  1. Type: Keras Deep Learning Network
    Keras Network
    The Keras deep learning network with an added Embedding layer.

Extension

The Keras Embedding Layer node is part of this extension:

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