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Test your understanding with targeted questions related to the topic.
Question 1
Easy
What does a contextual bandit allow an agent to do?
π‘ Hint: Think about why context is crucial for decision making.
Question 2
Easy
Name one algorithm discussed for tackling contextual bandit problems.
π‘ Hint: Consider which algorithm bases its decisions on linear models.
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 the fundamental concept behind contextual bandits?
π‘ Hint: Reflect on how context supports better decisions.
Question 2
LinUCB adapts to new data by using which technique?
π‘ Hint: Consider how a linear model functions.
Solve 3 more questions and get performance evaluation
Push your limits with challenges.
Question 1
Given a dataset of user interactions with ads, how would you implement an adaptive ad-selection mechanism using LinUCB? Outline the steps.
π‘ Hint: Focus on what context features would be pivotal for the algorithm.
Question 2
You are tasked with designing a campaign with Contextual Thompson Sampling. How would you model the reward distributions for various ads?
π‘ Hint: Think about the role of past performance in shaping current actions.
Challenge and get performance evaluation