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Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is a learning rate?
💡 Hint: Think about how quickly the model makes adjustments to errors.
Question 2
Easy
What does a Step Decay scheduler do?
💡 Hint: Consider the term 'step' in its name.
Practice 4 more questions and get performance evaluation
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
What does a scheduler in deep learning mainly affect?
💡 Hint: Focus on what a scheduler is designed to do.
Question 2
Is it true that learning rate warm-up starts with a high rate?
💡 Hint: Think about the term ‘warm-up’.
Solve 2 more questions and get performance evaluation
Push your limits with challenges.
Question 1
Evaluate a situation where a model trained with no scheduler fails to converge. Propose a scheduling strategy that could rectify this issue.
💡 Hint: Think about dynamically adjusting the learning pace.
Question 2
Create a hypothetical training scenario: describe initial learning rates and adjustments made by various schedulers. Analyze their impact on model performance.
💡 Hint: Consider how the model's learning evolves with each approach.
Challenge and get performance evaluation