Practice - Challenges
Practice Questions
Test your understanding with targeted questions
What happens if the learning rate is too high?
💡 Hint: Think about how adjustments affect the model's path.
Define 'local minima' and explain its significance.
💡 Hint: Consider the landscape analogy.
4 more questions available
Interactive Quizzes
Quick quizzes to reinforce your learning
What could happen if the learning rate is set too low?
💡 Hint: Remember the speed of convergence.
Local minima can mislead optimization because:
💡 Hint: Think about the landscape analogy of hills.
1 more question available
Challenge Problems
Push your limits with advanced challenges
You are training a neural network but notice it becomes inconsistent due to the learning rate. Describe a plan to adjust it and test its effectiveness.
💡 Hint: Consider automated approaches like learning rate schedules.
Explain how you would approach the situation where your model consistently gets stuck at a local minimum during optimization.
💡 Hint: Think creatively about initiating the optimization process.
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Reference links
Supplementary resources to enhance your learning experience.