Data Science and Machine Learning (Theory and Projects) A to Z - DNN and Deep Learning Basics: DNN What is Loss Function

The video tutorial introduces the concept of loss functions, focusing on squared loss and binary cross entropy loss. It explains the binary cross entropy loss function, commonly used in binary classification tasks, and provides an exercise to derive its expression. The exercise also involves validating the loss function by showing that it yields high loss values for incorrect predictions and low values for correct ones.

What is the significance of the binary cross entropy loss in binary classification?

What is the expression for binary cross entropy loss?

Can you explain why binary cross entropy is a loss function?

How does binary cross entropy loss behave when the prediction is wrong?

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