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

The video tutorial explains how to calculate the total number of weights in a neural network. It covers the process for each layer, including the input, hidden, and output layers. The tutorial emphasizes the importance of understanding the number of weights as it relates to model complexity and the risk of overfitting, especially with limited training data.

What new insight or understanding did you gain from this video?