Question

in a feedforward neural network with one hidden layer, each consisting of 10 neurons in the input layer, 5 neurons in the hidden layer, and 2 neurons in the output layer, how many parameters are there in total, including both weights and biases (assume all layers are fully-connected - dense layer)

Answer 1

In a fully connected feedforward neural network with one hidden layer, 10 neurons in the input layer, 5 neurons in the hidden layer, and 2 neurons in the output layer, there are a total of 67 parameters. This includes 60 weights and 7 biases.

Step-by-step explanation:

To calculate the total number of parameters in a feedforward neural network with one hidden layer, you need to account for all the weights and biases between each layer. The network described has 10 neurons in the input layer, 5 neurons in the hidden layer, and 2 neurons in the output layer.

The number of weights between the input and hidden layer is the product of the neurons in those layers, so there are 10 * 5 = 50 weights. Similarly, the number of weights between the hidden and output layer is 5 * 2 = 10 weights.

In addition to the weights, each neuron in the hidden and output layers has a bias term. Thus, there are 5 biases for the hidden layer and 2 biases for the output layer. In total, the network has 5 + 2 = 7 biases.

The total number of parameters is the sum of all weights and biases which is 50 + 10 + 7 = 67 parameters.