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AI QUIZ

Sumukh Hegde 10 preguntas

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Preguntas del test (10)

  1. 1Which of the following best describes the No Free Lunch Theorem in AI?
    1. AAI algorithms perform better when trained with more data
    2. BNo single algorithm is best for all problems
    3. CAI algorithms cannot surpass human intelligence
    4. DTraining AI models requires computational optimization
  2. 2 What is catastrophic forgetting in neural networks?
    1. AOverfitting to the training data
    2. BDeletion of weights during training
    3. CLoss of previously learned information when learning new tasks
    4. DMemory overflow during backpropagation
  3. 3 In Deep Q-Networks (DQN), what is the main purpose of the target network?
    1. ATo reduce training time
    2. BTo explore the environment
    3. CTo stabilize learning by fixing the Q-value targets
    4. DTo store policy gradients
  4. 4Which activation function is most prone to the dying neuron problem?
    1. ASigmoid
    2. BTanh
    3. CReLU
    4. DSwish
  5. 5What does the attention mechanism do in Transformer models?
    1. AA. Reduces model parameters
    2. BB. Assigns weights to input tokens based on relevance
    3. CC. Prevents overfitting
    4. DD. Compresses the input sequence
  6. 6Which technique is commonly used to deal with the vanishing gradient problem in RNNs?
    1. ADropout
    2. BGradient clipping
    3. CBatch normalization
    4. DLayer normalization
  7. 7In game-playing AI, the Minimax algorithm assumes that:
    1. ABoth players make optimal decisions
    2. BOnly one player uses a rational strategy
    3. CPlayers take random actions
    4. DThe game is stochastic in nature
  8. 8Which of the following models does not use the Markov property explicitly?
    1. AHidden Markov Model (HMM)
    2. BQ-learning
    3. CRecurrent Neural Network (RNN)
    4. DMarkov Decision Process (MDP)
  9. 9 In transfer learning, which layer of a pre-trained network is most commonly replaced or fine-tuned for a new task?
    1. AInitial convolutional layers
    2. BAll hidden layers
    3. COutput layer
    4. DPooling layer
  10. 10Which of the following is not a valid assumption in the Naive Bayes classifier?
    1. AFeatures are independent given the class
    2. BThe model uses Bayes' theorem
    3. CFeatures are conditionally dependent on each other
    4. DThe prior probabilities are used

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Descripción
Challenge your knowledge with this Advanced Artificial Intelligence Quiz designed for AI enthusiasts, developers, and students! This quiz features difficult multiple-choice questions covering deep learning, reinforcement learning, neural networks, and theoretical foundations like the No Free Lunch Theorem and Markov processes. Test your understanding of cutting-edge AI techniques and concepts with questions that go beyond the basics.
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