From the course: Training Neural Networks in C++ (2021)

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Multilayer perceptrons

Multilayer perceptrons - C++ Tutorial

From the course: Training Neural Networks in C++ (2021)

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Multilayer perceptrons

- [Instructor] Now we've come to the point when we'll talk about the multilayer perceptron. This is the best-known feedforward neural network and it's one of the oldest models of the brain. It consists of neurons organized in layers and the data traverses the network from input to output. This is typically sketched from left to right. Feedforward neural networks have a so-called fully connected architecture between layers of neurons. Here's an example. First, we have the input layer. It contains the inputs of the network, technically known as the input vector. This is the only layer that does not contain neurons. You can think of these elements as input terminals. This is important, especially for the implementation, so I'll say it again. You don't have to place neurons in this layer. Second, we have the set of hidden layers, which are composed of neurons. Notice how all neurons from the first hidden layer are taking in…

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