Practice - Optimization in Deep Learning
Practice Questions
Test your understanding with targeted questions
What is a non-convex loss surface?
💡 Hint: Think about how this impacts optimization.
Explain what vanishing gradients are.
💡 Hint: Consider the effect on learning speed.
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Interactive Quizzes
Quick quizzes to reinforce your learning
What do vanishing gradients lead to in deep learning?
💡 Hint: Consider what happens when gradients stop changing significantly.
True or False: Exploding gradients can cause numerical instability in a model.
💡 Hint: Recall how weight adjustments impact model training.
1 more question available
Challenge Problems
Push your limits with advanced challenges
You are training a deep neural network, and you notice that it gets stuck frequently during the training process. Outline a multi-step strategy to improve the situation, considering initialization, normalization, and architecture.
💡 Hint: Remember the key optimization techniques we've discussed.
Imagine a scenario where your model suffers from both exploding and vanishing gradients. How would you design your optimization approach to counter both issues?
💡 Hint: Draw from our discussion about the various techniques.
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Reference links
Supplementary resources to enhance your learning experience.