Artificial Intelligence (AI) MCQs with answers Page - 24

Here, you will find a collection of MCQ questions on Artificial Intelligence (AI). Go through these questions to enhance your preparation for upcoming examinations and interviews.

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Q. What does 'overfitting' refer to in AI?

  • (A) When a model is too simple
  • (B) When a model performs poorly on training data
  • (C) When a model memorizes training data but fails on new data
  • (D) When data is missing

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Q. Which technique helps reduce overfitting?

  • (A) Using more epochs
  • (B) Adding more layers
  • (C) Regularization
  • (D) Decreasing data

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Q. Which of the following is NOT a learning paradigm in AI?

  • (A) Supervised learning
  • (B) Unsupervised learning
  • (C) Predictive learning
  • (D) Reinforcement learning

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Q. Which AI algorithm is typically used for spam filtering?

  • (A) Naive Bayes
  • (B) KNN
  • (C) K-Means
  • (D) SVM

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Q. What is the goal of dimensionality reduction?

  • (A) Increase accuracy
  • (B) Reduce model size
  • (C) Remove irrelevant features
  • (D) Both b and c

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Q. What does 'AI bias' refer to?

  • (A) AI choosing between algorithms
  • (B) AI always giving the same answer
  • (C) AI making unfair or prejudiced decisions due to biased data
  • (D) A constant in machine learning

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Q. Which algorithm is used to reduce a large set of variables to a smaller set?

  • (A) SVM
  • (B) PCA
  • (C) KNN
  • (D) Naive Bayes

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Q. Which AI model component is responsible for making predictions?

  • (A) Optimizer
  • (B) Loss function
  • (C) Trained model
  • (D) Input data

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Q. Which of the following can help in improving AI model performance?

  • (A) More data
  • (B) Better features
  • (C) Hyperparameter tuning
  • (D) All of the above

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Q. Which neural network model allows data to flow in both directions?

  • (A) RNN
  • (B) Bidirectional RNN
  • (C) CNN
  • (D) Autoencoder

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