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A collection of questions and answers on machine learning algorithms.
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1. What is the difference between a value function and a policy in reinforcement learning?
2. What is the difference between a frequentist and a Bayesian approach to machine learning?
3. What is the purpose of a recurrent neural network?
4. What is the difference between a linear and a non-linear model?
5. What is the purpose of a support vector machine?
6. What is the purpose of a reinforcement learning algorithm?
7. What is the difference between a decision tree and a random forest?
8. What is the difference between an actor-critic and a policy gradient algorithm?
9. What is the difference between a classification and a regression model?
10. What is the purpose of a cost function in machine learning?
11. What is the purpose of a Q-learning algorithm?
12. What is the purpose of cross-validation in machine learning?
13. What is the difference between a neural network and a deep neural network?
14. What is the difference between a generative and a discriminative model?
15. What is the purpose of a Markov decision process?
16. What is the purpose of a Bayesian network?
17. What is the difference between an agent and an environment in reinforcement learning?
18. What is the difference between supervised and unsupervised learning?
19. What is the purpose of a regularization term in machine learning?