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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What does Adagrad do?
💡 Hint: Think about what happens when parameters are updated frequently.
Question 2
Easy
Name one benefit of using Adagrad.
💡 Hint: Focus on the stability aspect.
Practice 4 more questions and get performance evaluation
Interactive Quizzes
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
What is the main purpose of Adagrad?
- To provide a static learning rate for all parameters
- To adjust learning rates based on updates
- To use only first derivatives
💡 Hint: Consider how regular and abnormal updates affect learning.
Question 2
True or False: Adagrad can lead to very small learning rates over time.
- True
- False
💡 Hint: Think about how learning rates react to update frequencies.
Solve and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Given a learning rate of 0.1, and past gradients of [0.04, 0.01, 0.06], calculate the final learning rate adjustments.
💡 Hint: Remember to use the formula involving G in the denominator and apply it for each gradient.
Question 2
Describe a scenario in a machine learning project where using Adagrad might lead to better performance compared to static learning rate methods.
💡 Hint: Consider the implications of frequent updates versus rare feature abnormalities.
Challenge and get performance evaluation