Reinforcement Learning and Deep RL Python Theory and Projects - DNN What Is Loss Function Exercise Solution - 2

The video tutorial explains the concept of one-hot encoding for class labels, using examples to illustrate how target labels can be represented as vectors. It then discusses how predicted labels are presented as probability vectors through softmax. The tutorial further delves into the calculation of cross entropy loss, providing examples to clarify the process. Finally, it compares cross entropy loss with other loss functions, emphasizing the importance of choosing the right loss function as a hyperparameter for optimal performance.

What are the differences between cross entropy loss and binary cross entropy loss?

Why is the choice of loss function considered a hyperparameter, and how can it affect performance?