Q40. What is the primary objective of anomaly detection in artificial intelligence?
a) Identifying outliers or abnormalities in data
b) Maximizing accuracy in classification tasks
c) Minimizing computational resources
d) Achieving perfect precision and recall
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Correct Answer: a) Identifying outliers or abnormalities in data
Explanation: Anomaly Detection involves identifying outliers or abnormalities in data that deviate significantly from normal behavior, enabling tasks such as fraud detection, network intrusion detection, and fault diagnosis.
Q41. Which AI technique involves training a model on a large dataset with labeled examples to make predictions or decisions?
a) Unsupervised Learning
b) Reinforcement Learning
c) Supervised Learning
d) Semi-supervised Learning
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Correct Answer: c) Supervised Learning
Explanation: Supervised Learning involves training a model on a large dataset with labeled examples, where each input-output pair is explicitly provided, enabling the model to make predictions or decisions based on new, unseen examples.
Q42. What is the term for the process of adjusting the parameters of a machine learning model to minimize errors or maximize performance?
a) Optimization
b) Regularization
c) Training
d) Validation
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Correct Answer: a) Optimization
Explanation: Optimization in machine learning involves adjusting the parameters of a model to minimize errors or maximize performance metrics such as accuracy, precision, or recall, typically achieved through techniques like gradient descent.
Q43. Which of the following is a limitation of rule-based expert systems?
a) Difficulty in handling uncertainty
b) Inability to learn from data
c) Lack of scalability
d) All of the above
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Correct Answer: d) All of the above
Explanation: Rule-based expert systems may struggle with handling uncertainty, inability to learn from data, and lack of scalability, presenting significant limitations in certain applications compared to more flexible machine learning approaches.
Q44. Which AI application involves the use of algorithms to analyze and interpret human handwriting from images or documents?
a) Optical Character Recognition (OCR)
b) Sentiment Analysis
c) Natural Language Processing
d) Facial Recognition
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Correct Answer: a) Optical Character Recognition (OCR)
Explanation: Optical Character Recognition (OCR) utilizes artificial intelligence algorithms to analyze and interpret human handwriting or printed text from images or documents, converting it into machine-readable text for further processing or analysis.
Q45. What is the term for the process of automatically generating new data samples by modifying existing data?
a) Data Mining
b) Data Augmentation
c) Data Preprocessing
d) Data Cleaning
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Correct Answer: b) Data Augmentation
Explanation: Data Augmentation involves automatically generating new data samples by applying transformations or modifications to existing data, such as flipping, rotating, or adding noise, to increase the diversity and size of the dataset for training machine learning models.
Q46. Which AI technique involves the use of algorithms to extract structured information from unstructured textual data?
a) Sentiment Analysis
b) Named Entity Recognition
c) Topic Modeling
d) Text Summarization
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Correct Answer: b) Named Entity Recognition
Explanation: Named Entity Recognition (NER) is an AI technique that involves identifying and classifying named entities, such as names of people, organizations, locations, dates, and numerical expressions, within unstructured textual data.
Q47. What is the term for the process of training a machine learning model to perform a specific task using a large amount of labeled data?
a) Transfer Learning
b) Fine-tuning
c) Pretraining
d) Supervised Learning
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Correct Answer: d) Supervised Learning
Explanation: Supervised Learning involves training a machine learning model to perform a specific task, such as classification or regression, using a large dataset with labeled examples, where each input-output pair is explicitly provided during training.
Q48. Which AI technique involves simulating the behavior of a human expert to solve problems in a specific domain?
a) Reinforcement Learning
b) Genetic Algorithms
c) Expert Systems
d) Ant Colony Optimization
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Correct Answer: c) Expert Systems
Explanation: Expert Systems simulate the problem-solving behavior of human experts in specific domains by representing knowledge using rules or knowledge bases and using logical inference to derive conclusions and make decisions.
Q49. What is the term for the process of selecting the most relevant features or variables from a dataset for use in machine learning models?
a) Feature Engineering
b) Feature Selection
c) Dimensionality Reduction
d) Feature Extraction
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Correct Answer: b) Feature Selection
Explanation: Feature Selection involves identifying and selecting the most relevant features or variables from a dataset for use in machine learning models, aiming to improve model performance, reduce overfitting, and enhance interpretability.
Q50. Which of the following is a commonly used evaluation metric for classification tasks in machine learning?
a) Mean Absolute Error (MAE)
b) Root Mean Squared Error (RMSE)
c) Accuracy
d) R-squared (R^2)
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Correct Answer: c) Accuracy
Explanation: Accuracy is a commonly used evaluation metric for classification tasks in machine learning, representing the proportion of correctly classified instances out of the total number of instances in the dataset.