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AI/ML

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1. What function does the learning_rate parameter serve in the optimization of gradient descent?

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2. The condition that an algorithm is considered complete is _______________.

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3. Why is feature engineering used in machine learning?

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4. Which algorithm is employed by the game tree to determine a win or loss?

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5. Describe the meaning of "latent variables" in graphical models of probability.

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6. In LISP programming, the square root is entered as_____.

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7. What is the purpose of cross-validation in machine learning?

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8. What distinguishes recall from precision?

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9. What effect does a kernel selection have on a Support Vector Machine's (SVM) performance? 

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10.  What does the neural network training epochs parameter mean?

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11. In the context of decision trees, what does the term "entropy" mean?

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12. In LISP, the addition of 5+8 is entered as_______.

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13. How does the classification algorithm known as Support Vector Machine (SVM) operate?

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14. In the context of tree-based models such as Random Forests, what does feature importance mean?

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15. In terms of propositional logic, which claim is untrue?

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16. Why is feature scaling important in machine learning?

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17. What is the difference between bagging and boosting in ensemble learning?

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18. Which of the following statements about conditional probability is true?

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19. Why is regularization used in machine learning models?

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20. Which of the following describes an algorithm for unsupervised learning?

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21. State statement is valid for the Heuristic function

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22. Which of the subsequent describes a deterministic algorithm?

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23. What does the k-nearest neighbors (KNN) algorithm aim to achieve?

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24. How does the model's performance be affected by the bias-variance trade-off?

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25. What does the term "class label" mean in classification?

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26. What is supervised learning's main objective?

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27. Among the languages listed, which one is not frequently used for AI?

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28. The deepest point at which alpha-beta pruning can be implemented

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29. Who is credited with creating artificial intelligence?

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30. How does a confusion matrix fit into the classification process?

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31. What is the unsupervised learning application of the Expectation-Maximization (EM) algorithm?

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32. What is the purpose of the activation function in a neural network?

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33. When it comes to machine learning models, what does overfitting mean?

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34. A method created to ascertain whether a machine was capable of exhibiting the artificial intelligence known as the ___

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35. What part does the trade-off between exploration and exploitation play in reinforcement learning?

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36. Which of the following scenarios calls for the use of blind search?

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37. What does dropout in neural networks mean?

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38. When a hypothesis predicts a good outcome but the actual result is negative, this situation is referred to as _______.

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39. Knowledge in artificial intelligence can be expressed as _______.

i.Predicate Logic

ii.Propositional Logic

iii. Compound Logic

iv.Machine Logic

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40. What effect does the loss function selection have on a machine learning model's training process?

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