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Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is a non-convex function?
π‘ Hint: Think about the landscapes created by the graphs of these functions.
Question 2
Easy
What is a local minimum?
π‘ Hint: Relate it to the concept of peaks and valleys.
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 is a characteristic of non-convex functions?
π‘ Hint: Consider how these functions behave differently from convex functions.
Question 2
True or False: A saddle point is a minimum point.
π‘ Hint: Focus on the definition of saddle points and how they behave.
Solve and get performance evaluation
Push your limits with challenges.
Question 1
Propose a strategy for navigating a non-convex optimization landscape while training a neural network.
π‘ Hint: Think about methods that help keep the learning process dynamic.
Question 2
Imagine you are training a reinforcement learning agent. Describe how it might encounter non-convex optimization issues.
π‘ Hint: Consider scenarios where the agent can make multiple choices but may end up being suboptimal.
Challenge and get performance evaluation