If you are building a DNN, say, with two layers, and you want to use embeddings as one of your feature inputs, what's the best way to input the embedding?
I'm trying to understand if I should break the embeddings up so that every array value in the embedding becomes its own input feature to the model or whether the embedding should be kept in array form.
I've been following AirBnB's model for inspiration.
I'm trying to predict a binary classification in the final layer.