Deep learning is a subset of machine learning that leverages artificial neural network architectures. An artificial neural network (ANN) comprises layers of interconnected nodes, known as neurons, that collaboratively process and learn from input data.
In a deep neural network with full connectivity, there is an input layer followed by one or more hidden layers arranged sequentially. Each neuron in a given layer receives input from neurons in the preceding layer or directly from the input layer. The output of one neuron serves as the input for neurons in the subsequent layer, and this pattern continues until the final layer generates the network’s output. The network’s layers apply a series of nonlinear transformations to the input data, enabling it to learn complex representations of the data.