Reinforcement Learning and Deep RL Python Theory and Projects - DNN Loss Function in PyTorch

The video tutorial explains the use of activation functions in PyTorch, focusing on the sigmoid function. It demonstrates setting up a simple model and defining a loss function, specifically binary cross entropy loss. The tutorial emphasizes the importance of loss functions as a measure of model performance, showing how to calculate and interpret loss values. It also encourages exploring various loss functions available in PyTorch, preparing for the next topic on gradient descent.

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