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MCQ On Artificial Intelligence With Answers [Live]

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MCQs On Artificial Intelligence with Answer

1. Which of the following is the father of AI?

a) Alan Turing
b) Charles Babbage
c) John McCarthy
d) None of the above

2. Which of the following is an application of AI?

a) Game playing
b) Speech recognition
c) Robotics
d) All of the above

3. Which of the following is a component of AI?

a) Learning
b) Reasoning
c) Problem-solving
d) All of the above

4. Which of the following is the father of AI?

a) Alan Turing
b) Charles Babbage
c) John McCarthy
d) None of the above

5. Which of the following is an application of AI?

a) Game playing
b) Speech recognition
c) Robotics
d) All of the above

6. Which of the following is a component of AI?

a) Learning
b) Reasoning
c) Problem-solving
d) All of the above

7. What is the main goal of AI?

a) To create systems that think like humans
b) To create systems that think rationally
c) To create systems that act like humans
d) All of the above

8. Which of the following is a subfield of AI?

a) Neural networks
b) Genetic algorithms
c) Natural language processing (NLP)
d) All of the above

9. Which language is most commonly used in AI?

a) Python
b) Java
c) Lisp
d) Prolog

10. Which of the following is a learning technique in AI?

a) Supervised learning
b) Unsupervised learning
c) Reinforcement learning
d) All of the above

11. What does NLP stand for in AI?

a) Neural Language Processing
b) Natural Language Processing
c) Natural Linguistic Programming
d) None of the above

12. Which of the following is a type of machine learning?

a) Supervised learning
b) Unsupervised learning
c) Reinforcement learning
d) All of the above

13. Which of the following is an AI technique that simulates the brain’s neural networks?

a) Fuzzy logic
b) Neural networks
c) Genetic algorithms
d) Bayesian networks

14. What does “AI winter” refer to?

a) A period of reduced funding and interest in AI research
b) A season when AI projects are most active
c) A situation where AI systems overheat
d) None of the above

15. Which of the following is an example of weak AI?

a) Siri
b) Self-driving cars
c) AlphaGo
d) All of the above

16. In which year was the term “Artificial Intelligence” first coined?

a) 1956
b) 1943
c) 1965
d) 1972

17. Which of the following is NOT a type of AI?

a) Strong AI
b) Narrow AI
c) Weak AI
d) Virtual AI

18. What is the purpose of the Turing Test?

a) To measure a machine’s ability to exhibit intelligent behavior
b) To determine the speed of a computer
c) To test a machine’s capability to solve complex problems
d) To compare the performance of different AI algorithms

19. Which of the following is an example of a neural network?

a) Decision Tree
b) Convolutional Neural Network
c) Naive Bayes
d) K-Nearest Neighbors

20. What does “deep learning” refer to in AI?

a) A method of learning that involves deep contemplation
b) A subset of machine learning based on neural networks
c) Learning that requires a deep understanding of algorithms
d) None of the above

21. Which of the following is NOT a neural network architecture?

a) RNN (Recurrent Neural Network)
b) CNN (Convolutional Neural Network)
c) FNN (Forward Neural Network)
d) GAN (Generative Adversarial Network)

22. What is the primary function of an activation function in a neural network?

a) To activate neurons
b) To introduce non-linearity into the model
c) To determine the network’s architecture
d) To optimize the model’s parameters

23. Which of the following AI techniques is used in speech recognition?

a) Natural Language Processing (NLP)
b) Genetic Algorithms
c) Decision Trees
d) Swarm Intelligence

24. Which of the following is a type of unsupervised learning algorithm?

a) Linear Regression
b) K-Means Clustering
c) Decision Trees
d) Random Forest

25. What is the role of a loss function in a neural network?

a) To measure the performance of the model
b) To introduce non-linearity into the network
c) To update the weights of the network
d) To calculate the number of layers in the network

26. Which of the following is a common activation function used in neural networks?

a) Sigmoid
b) ReLU
c) Tanh
d) All of the above

27. What is “overfitting” in machine learning?

a) When the model performs well on training data but poorly on new data
b) When the model performs poorly on both training and new data
c) When the model underestimates the complexity of the data
d) When the model requires more data to perform well

28. What is “gradient descent” used for in training neural networks?

a) To initialize the weights of the network
b) To update the weights to minimize the loss function
c) To calculate the number of hidden layers
d) To generate new data points

29. What is “transfer learning” in AI?

a) Reusing a pre-trained model on a new but similar task
b) Transferring data from one model to another
c) Learning from data transferred between devices
d) None of the above

30. Which of the following is a method used to prevent overfitting in machine learning?

a) Cross-validation
b) Regularization
c) Data augmentation
d) All of the above

31. What is a common use case for reinforcement learning?

a) Image classification
b) Speech recognition
c) Game playing
d) None of the above

32. Which of the following describes a “convolutional layer” in a CNN?

a) A layer that applies filters to input data
b) A layer that connects every neuron to each other
c) A layer that performs dimensionality reduction
d) A layer that normalizes the data

33. What does “RNN” stand for in machine learning?

a) Recurrent Neural Network
b) Random Neural Network
c) Recursive Neural Network
d) None of the above

34. Which AI technique is commonly used in Natural Language Processing (NLP)?

a) Decision Trees
b) K-Nearest Neighbors
c) Hidden Markov Models
d) Linear Regression

35. What is the purpose of “dropout” in a neural network?

a) To increase the training time
b) To prevent overfitting by randomly dropping neurons
c) To reduce the complexity of the model
d) To improve the accuracy of the model

36. Which type of neural network is specifically designed for sequential data?

a) Convolutional Neural Network (CNN)
b) Recurrent Neural Network (RNN)
c) Feedforward Neural Network (FNN)
d) Generative Adversarial Network (GAN)

37. What is “precision” in the context of machine learning?

a) The ability to correctly classify positive instances
b) The ability to correctly classify negative instances
c) The ability to measure the accuracy of a model
d) The ability to measure the error rate of a model

38. Which of the following is a feature extraction technique in image processing?

a) Fourier Transform
b) Principal Component Analysis (PCA)
c) Histogram of Oriented Gradients (HOG)
d) All of the above

39. What does “backpropagation” refer to in neural networks?

a) The process of propagating errors backward to update weights
b) The process of forwarding information through the network
c) The method of generating new training data
d) None of the above

40. What is the primary purpose of a confusion matrix in machine learning?

a) To visualize the distribution of data
b) To evaluate the performance of a classification model
c) To measure the training time of a model
d) To determine the model’s complexity

41. What is the main goal of “unsupervised learning”?

a) To predict a target variable
b) To find hidden patterns or intrinsic structures in data
c) To improve supervised learning algorithms
d) To increase model complexity

42. In which scenario is a “Generative Adversarial Network (GAN)” typically used?

a) Classification of text data
b) Image generation
c) Sequence prediction
d) None of the above

43. What does “one-hot encoding” do in data preprocessing?

a) Converts categorical data into binary vectors
b) Normalizes numerical data
c) Reduces dimensionality of data
d) Applies scaling to data

44. Which machine learning model is typically used for binary classification tasks?

a) Linear Regression
b) Logistic Regression
c) K-Means Clustering
d) Decision Tree

45. What is “precision” in the context of classification metrics?

a) The ratio of correctly predicted positive observations to the total predicted positives
b) The ratio of correctly predicted positives to all actual positives
c) The difference between predicted and actual values
d) The rate of incorrectly predicted negative observations

46. What does “recall” measure in a classification model?

a) The ability of a model to find all relevant instances in a dataset
b) The ability of a model to ignore irrelevant instances
c) The difference between predicted and actual values
d) The total number of predictions made by the model

47. Which technique is used to deal with imbalanced datasets?

a) Random Oversampling
b) SMOTE (Synthetic Minority Over-sampling Technique)
c) Random Undersampling
d) All of the above

48. What is “dimensionality reduction” in machine learning?

a) Reducing the number of features or dimensions in the data
b) Increasing the number of features in the data
c) Changing the data format
d) Normalizing the data

49. Which algorithm is primarily used for “topic modeling” in NLP?

a) LSTM
b) Latent Dirichlet Allocation (LDA)
c) Random Forest
d) k-NN

50. What is the purpose of the “softmax” function in a neural network?

a) To activate neurons in a hidden layer
b) To normalize output to a probability distribution
c) To update weights during backpropagation
d) To initialize network parameters

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