Gradient descent updates weights to:
Answer options
A
Maximize loss
B
Minimize loss
C
Randomize weights
D
Always set weights to zero
Correct answer: Minimize loss
Explanation
Gradient descent iteratively updates model weights by moving in the direction that reduces the loss, using the gradient (partial derivatives) of the loss with respect to each weight.