1. What Are Unsupervised Machine Learning Techniques?
  2. What Is the Difference Between Supervised and Unsupervised Machine Learning?
  3. What Is the Difference Between Inductive Machine Learning and Deductive Machine Learning?
  4. Compare K-means and KNN Algorithms.
  5. What Is ‘naive’ in the Naive Bayes Classifier?
  6. Explain How a System Can Play a Game of Chess Using Reinforcement Learning.
  7. How Will You Know Which Machine Learning Algorithm to Choose for Your Classification Problem?
  8. When Will You Use Classification over Regression?
  9. How Do You Design an Email Spam Filter?
  10. What Is a Random Forest?
  11. Considering a Long List of Machine Learning Algorithms, given a Data Set, How Do You Decide Which One to Use?
  12. What Is Bias and Variance in a Machine Learning Model?
  13. What Is the Trade-off Between Bias and Variance?
  14. Define Precision and Recall.
  15. What Is Decision Tree Classification?

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