October 2018
Intermediate to advanced
472 pages
10h 57m
English
Content preview from Python Deep Learning Projects
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Defining a seq2seq model
In this section, we will outline the TensorFlow seq2seq model definition. We employed an embedding layer to go from integer representation to the vector representation of the input. This seq2seq model has four major components: the embedding layer, encoders, decoders, and cost/optimizers.
You can see the model in graphical form in the following diagram:
The TensorBoard visualization of the seq2seq model. This graph shows the connection between the encode and the decoder with other relevent components like the optimizer.
The following is a formal outline of the TensorFlow seq2seq model definition:
class Chatbot: def ...
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