MCQs

Disclaimer:

Educational Use Only:

The website links provided are to be used strictly for educational and knowledge-gaining purposes only.

No Misuse:

Do not misuse the links or the information contained therein for any commercial, illegal, or unethical activities.

Respect for Websites and Businesses:

Respect the intellectual property and business interests of the websites and their owners. Do not attempt to alter, copy, or redistribute content without proper authorization.

Acknowledge Value of Knowledge:

Recognize and value the knowledge and resources shared by these websites. Use the information responsibly and ethically.

No Endorsement:

The provision of these links does not imply endorsement of the linked sites, their content, or their products and services. Users are responsible for evaluating the suitability and accuracy of the information.

User Responsibility:

By accessing these links, you agree to use the information at your own risk and to comply with all applicable laws and website terms of use.

Overall MCQs for Reference

Which operation is considered a simple computation in AI?
a. Matrix addition
b. Image captioning
c. Strategy planning
d. Natural language understanding
Answer: ageeksforgeeks
What is typically the result of a simple classification task in AI?
a. A label or category
b. A logical formula
c. A story
d. A neural architecture
Answer: atutorialaicsip
Which of the following is NOT a simple computation in AI?
a. Addition of two numbers
b. Sorting a small list
c. Speech emotion recognition
d. Binary search
Answer: ctableau+1
Calculating the mean value of a dataset is an example of:
a. Data preprocessing
b. Feature engineering
c. Activation function
d. Logical inference
Answer: aexamradar
Which AI task uses basic distance computation as a core step?
a. K-nearest neighbor classification
b. Decision tree pruning
c. Sequence prediction
d. Text summarization
Answer: ageeksforgeeks
Which is the output of applying a sigmoid function in a simple neural network?
a. Value between 0 and 1
b. True or False
c. Class label
d. Integer value
Answer: ageeksforgeeks
What operation is used to scale features in data preprocessing?
a. Normalization
b. Clustering
c. Parsing
d. Embedding
Answer: aexamradar
Counting the frequency of words in a dataset is called:
a. Tokenization
b. Word embedding
c. Frequency analysis
d. Stopword removal
Answer: clinkedin
Which simple computation underpins clustering in K-means?
a. Euclidean distance calculation
b. Gradient descent
c. Matrix inversion
d. Information gain
Answer: ageeksforgeeks
In supervised learning, computing the error between target and prediction is called:
a. Loss calculation
b. Weight updating
c. Pruning
d. Sampling
Answer: ainterviewkickstart+1
What is the first step in simple AI problem solving?
a. Define the problem
b. Code the algorithm
c. Test the model
d. Interpret results
Answer: aplacementpreparation
If an algorithm assigns 0 to non-spam and 1 to spam, this is:
a. Binary classification
b. Regression
c. Reinforcement learning
d. Association mining
Answer: alinkedin+1
Which algorithm finds the shortest path in a graph?
a. Dijkstra’s algorithm
b. K-means
c. Apriori
d. ID3
Answer: ageeksforgeeks
Summing pixel intensities is often used in which task?
a. Image thresholding
b. Word prediction
c. Speech synthesis
d. Recommendation systems
Answer: atableau
Simple logical inference involves:
a. Applying rules to facts
b. Building deep neural nets
c. Running simulations
d. Compressing images
Answer: asanfoundry+1
The dot product is important in which AI computation?
a. Linear regression
b. Stemming
c. Clustering
d. Parsing
Answer: ageeksforgeeks
What is computed in least squares regression?
a. Sum of squared errors
b. Number of clusters
c. Text similarity
d. Path length
Answer: ageeksforgeeks
For two points (x1, y1) and (x2, y2), the distance is calculated using:
a. Euclidean distance formula
b. Manhattan distance formula
c. Cosine similarity
d. Jaccard index
Answer: ageeksforgeeks
What does “normalizing data” mean?
a. Scaling features to a similar range
b. Removing outliers
c. Encoding categorical labels
d. Building trees
Answer: aexamradar
Discretizing a continuous variable means:
a. Converting it into intervals or bins
b. Dividing an image
c. Slicing text
d. Merging clusters
Answer: aexamradar
What is the final step in a simple k-means clustering algorithm?
a. Assign points based on new centroids
b. Calculate entropy
c. Encode features
d. Prune tree
Answer: ageeksforgeeks
Which AI method is used to predict a numerical target value?
a. Regression
b. Classification
c. Clustering
d. Segmentation
Answer: atutorialaicsip+1
Merging two sorted lists into one is an example of:
a. Simple computation
b. Feature transformation
c. Model training
d. Convolution
Answer: asanfoundry
Squaring each value in a list is best described as:
a. Element-wise operation
b. Aggregation
c. Filtering
d. Regularization
Answer: asanfoundry
What computation is used to calculate cosine similarity?
a. Dot product and vector norm
b. Maximum value
c. Statistical median
d. Probability density
Answer: ageeksforgeeks
An “if-else” check is an example of:
a. Conditional statement computation
b. Normalization
c. Clustering
d. Tokenization
Answer: ascribd+1
What is one-hot encoding?
a. Representing categories with binary vectors
b. Sorting values
c. Normalizing data
d. Calculating distances
Answer: aexamradar
Adding noise to training data helps to:
a. Prevent overfitting
b. Increase error
c. Reduce feature size
d. Change algorithm
Answer: aexamradar
Calculating model “accuracy” is done by:
a. Ratio of correct predictions
b. Product of loss values
c. The mean of features
d. Cluster assignment
Answer: ainterviewkickstart+1
What computation is done in Principal Component Analysis (PCA)?
a. Eigenvalue decomposition
b. Sorting by median
c. Counting frequencies
d. Building trees
Answer: ageeksforgeeks
Which operation is performed to split a dataset?
a. Train-test split
b. Data encoding
c. Regularization
d. Ensemble averaging
Answer: alinkedin
Removing duplicate entries is known as:
a. Deduplication
b. Dimensionality reduction
c. Sampling
d. Prediction
Answer: aexamradar
Feature extraction typically involves:
a. Identifying useful attributes
b. Calculating probabilities
c. Normalizing loss
d. Combining datasets
Answer: aexamradar
Calculation of entropy in decision trees is:
a. Measurement of impurity
b. Output of clustering
c. Model updating
d. Indexing
Answer: ageeksforgeeks
Summing all items in a vector is called:
a. Aggregation
b. Feature selection
c. Regularization
d. Normalization
Answer: asanfoundry
Applying a softmax function gives:
a. Probabilities over classes
b. Feature vectors
c. Rule sets
d. Weights
Answer: alinkedin
Multiplying matrices is fundamental to:
a. Neural network layers
b. Parsing sentences
c. Clustering
d. Tokenizing text
Answer: alinkedin
In which computation do you convert numbers to text tokens?
a. Decoding
b. Aggregation
c. Clustering
d. Normalization
Answer: alinkedin+1
Simple rule-based AI uses:
a. IF-THEN logic
b. Deep learning architectures
c. Association rules
d. Fuzzy sets
Answer: ascribd+1
Finding the minimum or maximum is called:
a. Extreme value computation
b. Sampling
c. Stemming
d. Feature selection
Answer: asanfoundry
When you subtract the mean from each value, it is called:
a. Centering data
b. Binning
c. Predicting
d. Encoding
Answer: aexamradar
What operation is often used in convolutional neural networks?
a. Convolution
b. Thresholding
c. Histogram calculation
d. Sampling
Answer: alinkedin
Basic operation in “bag of words” is:
a. Counting word frequencies
b. Calculating medians
c. One-hot encoding
d. Building trees
Answer: alinkedin
Combining data samples is:
a. Aggregation
b. Clustering
c. Regularization
d. Feature reduction
Answer: asanfoundry+1
Selecting the highest probability class label involves:
a. Argmax computation
b. Normalization
c. Tokenization
d. Parsing
Answer: ainterviewkickstart+1
In k-NN, which computation is essential?
a. Distance measurement
b. Entropy calculation
c. Hyperplane fitting
d. Minimax search
Answer: ageeksforgeeks
Basic sorting algorithms in AI help with:
a. Data organization
b. Learning rates
c. Regularization
d. Parsing
Answer: asanfoundry
Calculating the mode is:
a. Finding the most frequent value
b. Reducing feature size
c. Normalizing
d. Clustering
Answer: ascribd
A fundamental operation in reinforcement learning is:
a. Reward calculation
b. Parsing input
c. Segmenting images
d. Normalizing weights
Answer: ageeksforgeeks
What is a “threshold” in binary classification?
a. Cut-off value for decision
b. Loss value
c. Regularization parameter
d. Cluster centroid
Answer: aexamradar

Blog

Systemethic Technologies

Leave a Reply Cancel reply

Useful links

Other Terms & Policies

Contact Info