Prevent Vanishing Gradients in Deep Networks
Company: Pinterest
Role: Machine Learning Engineer
Category: Machine Learning
Difficulty: hard
Interview Round: Technical Screen
Overview: Explain why gradients vanish in deep networks and how activation choice, initialization, residual connections, and normalization affect training. Distinguish optimization from regularization, use mathematical intuition, and discuss practical limitations across feed-forward and recurrent models.