Deep Learning CNN Convolutional Neural Networks with Python - Calculating Number of Weights of DNN Solution

The video tutorial explains the structure of a neural network's input hidden layer, detailing the number of inputs and the calculation of trainable parameters. It covers the breakdown of parameters for different neurons and concludes with a total count of 35 trainable parameters.

How many inputs does the first input hidden layer receive?

• 2 inputs

• 5 inputs

• 3 inputs

• 4 inputs

What is the total number of parameters for the first input hidden layer?

• 20 parameters

• 16 parameters

• 12 parameters

• 24 parameters

How many inputs are there for each of the three neurons discussed in the second section?

• 6 inputs

• 5 inputs

• 4 inputs

• 3 inputs

What is the total number of parameters for the neurons with five inputs each?

• 25 parameters

• 10 parameters

• 15 parameters

• 20 parameters

What is the total number of trainable parameters in the network?

• 35 parameters

• 32 parameters

• 30 parameters

• 40 parameters