Could you elaborate on the significance of training and loss graphs in a neural network? What are some commonly used loss functions in this context, and how do they affect the shape of the loss graph? In what ways do the training and loss graphs differ, and how do they contribute towards optimizing and enhancing model performance?
Machine Learning Engineer
Palo Alto Networks
Airbnb
Akamai
Deloitte
Slack
HubSpot
Interview question asked to Machine Learning Engineers interviewing at Avito, Epic Games, Nubank and others: Could you elaborate on the significance of training and loss graphs in a neural network? What are some commonly used loss functions in this context, and how do they affect the shape of the loss graph? In what ways do the training and loss graphs differ, and how do they contribute towards optimizing and enhancing model performance?.