What do the training and loss graphs imply for a neural network? How do various loss functions affect the shape of the loss graph, and what are some commonly employed ones? Can you discuss the dissimilarities between the training and loss graphs, and how they aid in model optimization and performance?

Interview question asked to Machine Learning Engineers interviewing at Discord, Bolt, Spotify and others: What do the training and loss graphs imply for a neural network? How do various loss functions affect the shape of the loss graph, and what are some commonly employed ones? Can you discuss the dissimilarities between the training and loss graphs, and how they aid in model optimization and performance?.