Practice - Advanced Gradient-Based Optimizers
Practice Questions
Test your understanding with targeted questions
What is momentum in optimization?
💡 Hint: Think of momentum as keeping you moving in the direction of your last update.
What does Adagrad do?
💡 Hint: Consider how frequently a parameter has been modified.
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Interactive Quizzes
Quick quizzes to reinforce your learning
What does momentum do in optimization?
💡 Hint: Remember how momentum increases forward movement.
True or False: Nesterov Accelerated Gradient does not consider previous updates.
💡 Hint: Think about predictions versus reactions.
2 more questions available
Challenge Problems
Push your limits with advanced challenges
Consider a model that struggles to converge using standard gradient descent. How would you choose an optimizer from those discussed and why?
💡 Hint: Consider the advantages of adapting learning rates and smoothing updates.
If given a dataset with highly variable features, which optimizer would you prefer and why?
💡 Hint: Think about which methods thrive in noisy landscapes.
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Reference links
Supplementary resources to enhance your learning experience.