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

The video tutorial introduces the concept of squared loss and binary cross entropy loss, focusing on their application in binary classification. An exercise is provided to derive the expression for binary cross entropy loss and demonstrate its properties, such as high loss for incorrect predictions and low loss for correct ones.

What is the expression for binary cross entropy loss?

Explain why binary cross entropy loss is considered a loss function.

What happens to the loss value when the prediction is wrong?

How does the value of binary cross entropy loss change based on the correctness of the prediction?

What is the significance of a low loss value in the context of binary classification?