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

The video tutorial explains the concept of one-hot encoding for class labels, where each class is represented by a vector with a single high (1) value and the rest low (0). It then discusses how predicted labels are presented as probability vectors using softmax. The tutorial further details the calculation of cross entropy loss, which measures the difference between predicted and true labels. Finally, it compares cross entropy loss with binary cross entropy loss, emphasizing the importance of choosing the right loss function as a hyperparameter for model performance.

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

Evaluate responses using AI:

OFF