From the course: Deep Learning with Python and Keras: Build a Model for Sentiment Analysis

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Training a DNN using embeddings

Training a DNN using embeddings

From the course: Deep Learning with Python and Keras: Build a Model for Sentiment Analysis

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Training a DNN using embeddings

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- [Narrator] We now have our vectorized layer set up to produce integer sequences to represent our input text. This is what we'll feed into the embeddings layer of our neural network in order to train embeddings to represent our input text. But first, I'm going to set up a few additional configuration options for my neural network training. This is the callback_list. Callbacks and Keras are a set of functions that can be applied at various stages during the training of a neural network model. Callbacks can be used to customize and monitor the training process by specifying actions that can be taken when specific events or conditions occur during training. I've specified two callbacks here. The first is EarlyStopping. This is the first callback in my list. The EarlyStopping callback stops training when the validation loss is no longer improving, and it saves the best model obtained during training. The monitor argument in…

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