Artificial Intelligence and Machine Learning MCQs | STS IBA FPSC BPSC SPSC PPSC Mcqs Test Preparation

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Which algorithm is commonly used for ‘text classification’?

A. Naive Bayes
B. K-means Clustering
C. Principal Component Analysis (PCA)
D. Support Vector Machine (SVM)

Answer: Naive Bayes

What is the purpose of ‘feature engineering’?

A. To create new features or modify existing features to improve model performance
B. To select the most relevant features from the dataset
C. To scale the features of the dataset
D. To handle missing values in the data

Answer: To create new features or modify existing features to improve model performance

What is ‘activation function’ in neural networks?

A. A function that introduces non-linearity into the model
B. A function that optimizes the model parameters
C. A function that scales the features
D. A function that reduces the dimensionality of the data

Answer: A function that introduces non-linearity into the model

What does ‘clustering’ involve in machine learning?

A. Grouping similar data points into clusters
B. Predicting outcomes based on input features
C. Finding the best model for a dataset
D. Optimizing model parameters

Answer: Grouping similar data points into clusters

Which algorithm is commonly used for ‘reinforcement learning’?

A. Q-learning
B. Principal Component Analysis (PCA)
C. K-means Clustering
D. Naive Bayes

Answer: Q-learning

What is the purpose of ‘hyperparameter tuning’?

A. To find the best configuration of hyperparameters for improving model performance
B. To select the most relevant features from the dataset
C. To reduce the dimensionality of the data
D. To handle missing values in the dataset

Answer: To find the best configuration of hyperparameters for improving model performance

Which of the following is a common application of ‘convolutional neural networks’ (CNNs)?

A. Image recognition and classification
B. Natural Language Processing
C. Reinforcement Learning
D. Dimensionality Reduction

Answer: Image recognition and classification

What does ‘batch normalization’ help with in deep learning models?

A. Accelerating the training process and improving model stability
B. Reducing the number of layers in the network
C. Increasing the number of training epochs
D. Improving feature selection

Answer: Accelerating the training process and improving model stability

Which of the following techniques is used to evaluate the performance of a classification model?

A. Confusion Matrix
B. Principal Component Analysis (PCA)
C. K-means Clustering
D. Mean Squared Error (MSE)

Answer: Confusion Matrix