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?

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

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

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

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

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