A dense layer is a type of layer in a neural network that is composed of neurons that are fully connected to the previous layer. In a dense layer, each neuron is connected to every neuron in the previous layer. This type of layer is also known as a fully connected layer or a fully connected neural network layer.
A dense layer is a key component of a neural network, as it is responsible for transforming the input data into a form that the neural network can use to make predictions. The neurons in the dense layer are responsible for learning the patterns in the data and creating a representation of the data that the neural network can use to make predictions.
The dense layer is typically the first layer in a neural network, as it is responsible for transforming the raw input data into a form that the neural network can use to make predictions. The neurons in the dense layer are responsible for learning the patterns in the data and creating a representation of the data that the neural network can use to make predictions.
The dense layer is typically followed by a pooling layer, which is used to reduce the dimensionality of the data by combining the outputs of the neurons in the dense layer. This reduces the amount of data that the neural network has to process, making it more efficient.
The dense layer is a key component of a neural network, as it is responsible for transforming the raw input data into a form that the neural network can use to make predictions. The neurons in the dense layer are responsible for learning the patterns in the data and creating a representation of the data that the neural network can use to make predictions.