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

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Feed forward neural networks

Feed forward neural networks

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

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Feed forward neural networks

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- [Instructor] In this movie, we'll discuss using deep learning models for working with text data, starting with dense neural networks that are feedforward neural networks. Feedforward neural networks are networks where the output of one layer is fed in as an input to the next layer in sequence, every neuron in a layer is connected to each neuron in the layer that follows. So here is an example of a feedforward neural network where we have an input layer, a hidden layer, and an output layer. Whatever input data you are feeding into the neural network is fed into the first layer of the model, that is the input layer. The data is transformed in the feedforward neural network, and you get your final output from the last layer in the model. Now, this final output depends on what kind of model you are training. If you're training a classification model that will predict a class or a category, the output will be probability…

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