STUDENT
AI - ADVANCED CONCEPTS OF MODELING
Total Q: 51
Time: 60 Mins
Q 1.
A program is designed to classify fruits based on size and color. What kind of learning is this?
Reinforcement Learning
Supervised Learning
Unsupervised Learning
Rule-based Learning
Q 2.
Which approach helps AI learn from rewards and punishments?
Supervised Learning
Reinforcement Learning
Rule-Based Learning
Unsupervised Learning
Q 3.
What does CNN stand for in Deep Learning?
Central Neural Network
Coded Neural Network
Convolutional Neural Network
Controlled Neural Network
Q 4.
You are training a model to detect spam emails. What kind of data do you need to provide for training?
Unlabeled data only
A list of email IDs
Labeled data showing which emails are spam or not
Photos of inbox folders
Q 5.
You are using past temperature data to predict tomorrow's temperature. Which model would be appropriate?
Classification Model
Clustering Model
Regression Model
Association Model
Q 6.
Observe the given graph and fill in the blank:
__________ the neural network, better is the performance.
Larger
Smaller
Medium
Traditional ML
Q 7.
Divya was learning neural networks. She understood that there were three layers in a neural network. Help her identify the layer that does processing in the neural network.
Output layer
Hidden layer
Input layer
Data layer
Q 8.
A business problem wherein we categorize whether an observation is "Safe", "At-Risk" or "Unsafe" is an example of
Classification
Clustering
Regression
Dimensionality Reduction
Q 9.
Assertion(A) : Neural networks are the backbone of deep learning algorithms
Reason(R): Neural networks use vast amounts of data
Both A and R are correct and R is the correct explanation of A
Both A and R are correct but R is NOT the correct explanation of A
A is correct but R is not correct
A is not correct but R is correct.
Q 10.
In reinforcement learning, the computer learns by:
Reading textbook examples
Following static rules
Trial and error using reward or penalty
Labeling the data itself
Q 11.
Which of the following best defines Machine Learning?
A program that runs without human input.
A model that mimics human brain neurons.
A method where machines learn from data without being explicitly programmed.
A data compression method.
Q 12.
A _______________is divided into multiple layers and each layer is further divided into several blocks called nodes.
Neural Networks
Convolutional Neural Network (CNN)
Machine learning algorithm
Hidden Layers
Q 13.
Which of the following is an example of a classification model?
Predicting house prices
Predicting tomorrow's temperature in
°
C
Classifying emails as spam or not spam
Predicting rainfall in millimeters
Q 14.
Which of the following is a correct feature of Neural network?
It can improve efficiency of two models.
It is useful with small dataset.
They are modelled on human brains and nervous system.
They need human intervention.
Q 15.
What is the main drawback of a rule-based AI model?
It improves over time
It works only with images
It is not trainable
It cannot learn from new data or feedback
Q 16.
AI is called a big umbrella because:
It only includes robotics.
It includes all types of data analysis.
It covers different technologies like ML and DL.
It only includes smart assistants.
Q 17.
For better efficiency of an AI project Training data should be _______
i) Relevant
ii) Scattered
iii) Structured
iv) Authentic
Choose the correct option:
Both i and ii
Both i and iv
Only i
Only iv
Q 18.
Labeled data means:
Data that is hidden from the model
Data with predefined tags or outcomes
Data stored in images only
Data that cannot be used in AI
Q 19.
Which form of unsupervised learning does the following diagram indicate?
Clustering
Regression
Reinforcement learning
Classification
Q 20.
Rule-based AI fails when:
It is trained on large datasets
The training data changes and model can't adapt
Labeled data is provided
Reinforcement signals are given
Q 21.
Assertion(A) : Neural networks are the backbone of deep learning algorithms
Reason(R): Neural networks use vast amounts of data
Both A and R are correct and R is the correct explanation of A
Both A and R are correct but R is NOT the correct explanation of A
A is correct but R is not correct
A is not correct but R is correct
Q 22.
Which AI learning method works on discovering patterns from unlabeled data?
Supervised Learning
Reinforcement Learning
Rule-Based Learning
Unsupervised Learning
Q 23.
Identify the algorithm based on the given graph
Dimensionality reduction
Classification
Clustering
Regression
Q 24.
In this learning model, the data set which is fed to the machine is labelled. Name the model.
Supervised Learning
Unsupervised Learning
Rule Based Learning
label Based Learning
Q 25.
What is the output of an Artificial Neural Network (ANN)?
Raw data
Final result after all processing layers
Only errors in data
Input data in different format
Q 26.
In supervised learning, the model is trained using:
Only output data
Labeled input data
Unlabeled data
Reinforcement signals
Q 27.
In the context of data, which term refers to the columns of a dataset?
Labels
Features
Rows
Clusters
Q 28.
What is the function of the hidden layers in a neural network?
They store user data
They display the result
They process and transform the data
They act as input devices
Q 29.
The 2 types of Supervised Learning models are
Classification and Regression
Clustering and Dimensionality Reduction
Rule Based and Learning Based
Classification and Clustering
Q 30.
Which of the following is an example of deep learning?
Filtering spam emails
Recommending friends on Facebook
Recognizing a person's face in a photo
Summarizing a news article
Q 31.
It refers to the unsupervised learning algorithm which can cluster the unknown data according to the patterns or trends identified out of it.
Regression
Classification
Clustering
Dimensionality reduction
Q 32.
Smita is working on a project that involves over a lakh of records. Which of the following should she use to make the best project?
Traditional programming
Manual processing
IoT
Neural networks
Q 33.
Deep Learning is preferred over Machine Learning when:
The dataset is small
The problem involves basic rules only
The dataset is large and complex
Manual coding is required
Q 34.
The process of attaching meaning or tags to data is called:
Labeling
Clustering
Associating
Grouping
Q 35.
CNN is best used for:
Identifying the price of vegetables
Solving MCQs
Image recognition tasks
Generating passwords
Q 36.
Which type of learning uses a reward-based feedback system?
Supervised Learning
Unsupervised Learning
Reinforcement Learning
Deep Learning
Q 37.
Which of the following is correct about the rule based approach?
We cannot provide enough rules to the machine.
A drawback/feature for this approach is that the learning is static.
Once the rules are fed into the system, it takes into consideration any changes made in the original training dataset.
It can improve itself based on the feedbacks.
Q 38.
Statement 1: There are four layers in a neural network.
Statement2: The first layer of the neural network is known as the output layer.
Both Statement1 and Statement2 are correct
Both Statement1 and Statement2 are incorrect
Statement1 is correct but Statement2 is incorrect
Statement2 is correct but Statement1 is incorrect
Q 39.
What does a Neural Network consist of?
Only input and output layers
Fixed rules and if-else logic
Layers made up of nodes that process data
Unlabeled training data only
Q 40.
A student trains a model using a dataset of labeled handwritten digits and then tests it on new digit images. What is being performed in the second step?
Training
Labeling
Testing
Clustering
Q 41.
Which of the following is the most advanced form of Artificial Intelligence?
Machine Learning
Rule-Based Model
Deep Learning
Reinforcement Learning
Q 42.
If Data is represented as "Answer", Processing is represented as "Data" and Answer is represented as "Processing", which of the following can be related to the description of layers in a neural network? Choose the correct options
Input Layer -> Data; Output layer -> Processing; Hidden Layer -> Answer
Input Layer -> Processing; Output layer -> Data; Hidden Layer -> Answer
Input Layer -> Answer; Output layer -> Processing; Hidden Layer -> Data
Input Layer -> Answer; Output layer ->Data; Hidden Layer -> Processing
Q 43.
Which of the following contributes to the efficiency of an AI project ?
High Model Complexity
Relevant and Authentic Training Data
Minimal Preprocessing
Limited Hardware Resources
Q 44.
Which neural network layer is responsible for receiving raw data input?
Hidden Layer
Output Layer
Processing Layer
Input Layer
Q 45.
Which model is best for predicting continuous values like house price?
Classification
Association
Regression
Clustering
Q 46.
It refers to the unsupervised learning algorithm which can cluster the unknown data according to the patterns or trends identified out of it.
Regression
Classification
Clustering
Dimensionality reduction
Q 47.
Which one of the following is a key feature of unsupervised learning?
Requires labeled data
Learns from predefined rules
Finds hidden patterns in data
Uses reward-based learning
Q 48.
While training a model on face images, you realize the model performs poorly with new faces. What should you check first?
Size of the image files
Quality of labels in training data
Brightness of your computer screen
Printer compatibility
Q 49.
In which learning type does the machine discover patterns in unlabeled data?
Supervised Learning
Reinforcement Learning
Deep Learning
Unsupervised Learning
Q 50.
Regression is one of the type of supervised learning model, where data is classified according to labels and data need not to be continuous.
True
False
-
-
Q 51.
Aman want to make an Artificially Intelligent system which can predict the salary of any employee based on his previous salaries. He has to feed the data of his previous salaries. This is the data with which the machine can be trained. The previous salary data here is known as_______ while the next salary prediction data set is known as the ________
Testing Data, Training Data
Training Data, Testing Data
Training Data, Next Data
First Data, Testing Data