layer_dense

A dense layer in a neural network is a type of layer where each neuron in the layer is connected to every neuron in the previous layer. This is also known as a fully connected layer.

In a dense layer, each neuron receives input from all the neurons in the previous layer and produces an output which is then passed to all the neurons in the next layer. The output of each neuron is calculated using a weighted sum of the inputs plus a bias term, which is then passed through an activation function.

A dense layer is typically used for the final classification or regression output in a neural network, where it maps the learned representations from the previous layers to the output labels or values. It can also be used in intermediate layers to extract complex features from the input data.

The number of neurons in a dense layer and the number of dense layers in a neural network are hyperparameters that can be tuned during model training to optimize performance.