Reinforcement Learning and Deep RL Python Theory and Projects - DNN Architecture Exercise

The video tutorial explains the concept of parameters or weights in a deep neural network. It uses a simple example with three features and two layers to illustrate the structure of a neural network. The tutorial details the number of neurons in each layer and emphasizes the importance of counting the total number of weights, which are the parameters of the network. A hint is provided to focus on an extra edge when calculating parameters, with a promise to reveal the solution in the next video.

What are the features mentioned in the example of the deep neural network?

How many layers are there in the described neural network, and how many neurons are in each layer?

What is the significance of weights in the neurons of a neural network?

What is the goal when counting the total number of weights in a neural network?

What hint is provided for computing the number of parameters in the neural network?