What is the primary purpose of a loss function in training neural networks?
Answer options
A
To define the network's architecture
B
To speed up training
C
To quantify the difference between predicted and actual
D
values
E
To initialize weights
F
To activate neurons
Correct answer: To quantify the difference between predicted and actual, values
Explanation
The primary purpose of a loss function is to quantify the difference between the model's predicted output and the actual (ground truth) values. This scalar error signal drives backpropagation and weight updates during training. Options [2] and [3] together form the complete answer: 'To quantify the difference between predicted and actual values.'