a diagram of a fully connected neural network. A fully connected neural network is a type of neural network in which each neuron is connected to every other neuron in the network.
The image shows a neural network with two hidden layers. The input layer consists of 100 neurons, each representing a feature of the input data. The first hidden layer consists of 70 neurons, and the second hidden layer consists of 50 neurons. The output layer consists of four neurons, each representing a possible output of the network.
The neurons in the network are connected by weighted edges. The weights are used to determine how much influence each neuron has on the other neurons.
Fully connected neural networks are a powerful tool for a variety of tasks, including image classification, natural language processing, and speech recognition.
