Quiz | Croma Campus

Which type of neural network is commonly used for image recognition tasks?

Convolutional Neural Network (CNN)
Recurrent Neural Network (RNN)
Multilayer Perceptron (MLP)
Radial Basis Function Network (RBFN)

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What is the purpose of the 'exploration' phase in reinforcement learning?

To exploit the current knowledge
To gather new information
To update the policy
To evaluate the reward function

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Which technique is used to make decisions in uncertain and complex environments?

Fuzzy Logic
Genetic Algorithms
Reinforcement Learning
Bayesian Networks

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Which AI technique focuses on enabling computers to learn from data and improve performance over time without being explicitly programmed?

Expert Systems
Machine Learning
Natural Language Processing
Robotics

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Which technique is used to recommend items to users based on their past preferences?

Clustering
Collaborative Filtering
Association Rule Learning
Regression

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Which technique is used to evaluate the importance of each feature in a machine learning model?

Feature Selection
Feature Extraction
Feature Engineering
All of the above

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Which of the following is an unsupervised learning algorithm?

Decision Trees
K-Means
Naive Bayes
Random Forest

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What is the main drawback of oversampling techniques?

Increased risk of overfitting
Decreased computational efficiency
Loss of information
Sensitivity to outliers

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What is the main objective of feature scaling in machine learning?

To reduce the number of features
To increase the complexity of the model
To increase the complexity of the model
To ensure that all features have the same scale

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Which technique is used to generate human-like outputs from a computer program?

Expert Systems
Genetic Algorithms
Natural Language Generation (NLG)
Reinforcement Learning

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Which technique is used to minimize errors in a neural network by adjusting the weights of connections between neurons?

Backpropagation
Gradient Descent
Forward Propagation
Stochastic Gradient Descent

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What is the purpose of dimensionality reduction in machine learning?

To increase the complexity of the model
To reduce overfitting
To decrease computational efficiency
To increase computational efficiency

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Which technique is used to evaluate the performance of a classification model across different thresholds?

Receiver Operating Characteristic (ROC) Curve
Precision-Recall Curve
Confusion Matrix
All of the above

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Which algorithm is used to find the shortest path in a graph?

Breadth-First Search (BFS)
Depth-First Search (DFS)
Dijkstra's Algorithm
A* Algorithm

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What is the main purpose of a confusion matrix?

To visualize the performance of a classification model
To calculate the accuracy of a regression model
To estimate the confidence interval of a prediction
To measure the variance of a model

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Which technique is used to transform categorical variables into numerical values?

Label Encoding
One-Hot Encoding
Ordinal Encoding
All of the above

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Which of the following is NOT a component of an expert system?

Knowledge Base
Inference Engine
User Interface
Deep Learning

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Which technique is used to assign probabilities to each possible value of a discrete random variable?

Probability Mass Function (PMF)
Probability Density Function (PDF)
Cumulative Distribution Function (CDF)
Cumulative Distribution Function (CDF)

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What is the primary objective of Artificial Intelligence (AI)?

To replace human intelligence
To mimic human intelligence in machines
To develop systems that can perform tasks requiring human intelligence
To automate all human tasks

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What is the main advantage of ensemble learning algorithms?

Reduced computational complexity
Improved predictive performance
Increased interpretability
Lower risk of overfitting

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Which ensemble learning algorithm combines the predictions of multiple base estimators?

Bagging
Boosting
Stacking
All of the above

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What is the main drawback of the K-Means clustering algorithm?

Sensitivity to outliers
High computational complexity
Difficulty in determining the number of clusters
Lack of scalability

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What is the term used to describe the difference between predicted values and actual values in regression analysis?

Error
Loss
Residual
Deviance

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What is the main drawback of rule-based expert systems?

Limited scalability
Difficulty in knowledge acquisition
Inability to handle uncertainty
High computational complexity

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Which technique is used to reduce the complexity of a decision tree model and avoid overfitting?

Pruning
Splitting
Growing
Branching

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Which of the following is NOT a subfield of AI?

Natural Language Processing (NLP)
Robotics
Calculus
Machine Learning

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What is the purpose of the activation function in a neural network?

To increase computational efficiency
To reduce overfitting
To introduce non-linearity
To normalize input data

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Which technique is used to measure the similarity between two documents?

Cosine Similarity
Euclidean Distance
Manhattan Distance
Jaccard Similarity

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Which approach in AI focuses on mimicking the evolutionary process to solve complex problems?

Expert Systems
Genetic Algorithms
Fuzzy Logic
Bayesian Networks

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Which of the following is NOT a characteristic of an artificial neural network?

Learning
Adaptability
Fuzzy Logic
Generalization

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