Practice Thompson Sampling - 9.8.3.4 | 9. Reinforcement Learning and Bandits | Advance Machine Learning
K12 Students

Academics

AI-Powered learning for Grades 8–12, aligned with major Indian and international curricula.

Academics
Professionals

Professional Courses

Industry-relevant training in Business, Technology, and Design to help professionals and graduates upskill for real-world careers.

Professional Courses
Games

Interactive Games

Fun, engaging games to boost memory, math fluency, typing speed, and English skillsβ€”perfect for learners of all ages.

games

9.8.3.4 - Thompson Sampling

Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What is Thompson Sampling primarily used for?

πŸ’‘ Hint: Think about how it balances trying new options versus sticking to familiar ones.

Question 2

Easy

What does Bayesian approach help in Thompson Sampling?

πŸ’‘ Hint: Consider how new data influences your conclusions.

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 does Thompson Sampling primarily address?

  • Exploration-Exploitation Dilemma
  • Data Collection Methods
  • Data Analysis Techniques

πŸ’‘ Hint: Recall the challenges faced in reinforcement learning.

Question 2

True or False: In Thompson Sampling, the exploration of arms is purely random.

  • True
  • False

πŸ’‘ Hint: Consider how actions are selected based on information rather than random chance.

Solve and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

In a MAB scenario with three arms, describe how you would implement Thompson Sampling and evaluate its performance after 100 trials.

πŸ’‘ Hint: Consider how to represent the prior and update based on results.

Question 2

Discuss the implications of using Thompson Sampling in a real-time application, such as web advertising. What challenges would you anticipate?

πŸ’‘ Hint: Think about how the algorithm would respond to user interactions over time.

Challenge and get performance evaluation