Reimagining Plutarch with Tensorflow 2.0

In the model summary we'll see that the number of parameters for the embedding layer is 2,024,200, which is 20,242 words times the embedding dimension of 100. The previously mentioned TensorFlow tutorial is using a reviews dataset with each of the reviews being labeled 1 or 0 depending on the positive or negative sentiment. We do not have the labeling luxury but still want to test drive this model, so will simply create an array of 0s and attach to each of the sentences; the model requires such a structure. This will not be the first or the last time that machine intelligence gets assaulted with an unsolvable task yet still obliges us with a solution.