STUDENT
AI - AI PROJECT CYCLE
Total Q: 33
Time: 30 Mins
Q 1.
4Ws Problem Canvas is a part of :
Problem Scoping
Data Acquisition
Modelling
Evaluation
Q 2.
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 3.
Choose the five stages of AI project cycle in correct order
Evaluation -> Problem Scoping -> Data Exploration -> Data Acquisition -> Modelling
Problem Scoping -> Data Exploration -> Data Acquisition -> Evaluation -> Modelling
Data Acquisition -> Problem Scoping -> Data Exploration -> Modelling -> Evaluation
Problem Scoping -> Data Acquisition -> Data Exploration -> Modelling -> Evaluation
Q 4.
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 5.
Which form of unsupervised learning does the following diagram indicate?
Clustering
Regression
Reinforcement learning
Classification
Q 6.
___________ is the last stage of the AI project Life cycle.
Problem Scoping
Evaluation
Modelling
Data Acquisition
Q 7.
The _______ representation makes the data understandable for humans as we can discover trends and patterns out of it.
Visual
Pattern
Image
Video
Q 8.
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 9.
Rajat has made a model which predicts the performance of Indian Cricket players in upcoming matches. He collected the data of players' performance with respect to stadium, bowlers, opponent team and health. His model works with good accuracy and precision value. Which of the statement given below is
incorrect
?
Data gathered with respect to stadium, bowlers, opponent team and health is known as Testing Data.
Data given to an AI model to check accuracy and precision is Testing Data.
Training data and testing data are acquired in the Data Acquisition stage.
Training data is always larger as compared to testing data.
Q 10.
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 11.
The _______Sustainable Development Goals (SDGs) were launched at the United Nations Sustainable Development Summit in New York in the year 2015, forming the 2030 Agenda for Sustainable Development.
17
15
13
19
Q 12.
The 4 W's Problem Canvas helps in identifying the key elements related to the given problem.
Which of the following is NOT one of the blocks of the Problem Canvas?
When
What
Where
Why
Q 13.
The 2 types of Supervised Learning models are
Classification and Regression
Clustering and Dimensionality Reduction
Rule Based and Learning Based
Classification and Clustering
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.
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 16.
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 17.
Which of the following is not part of the AI Project Cycle?
Data Exploration
Modelling
Testing
Problem Scoping
Q 18.
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 19.
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 20.
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 21.
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 22.
During Data Acquisition, feeding previous data into machine is called :
Training Data
Predicting Data
Testing Data
Evaluating Data
Q 23.
Observe the given graph and fill in the blank:
__________ the neural network, better is the performance.
Larger
Smaller
Medium
Traditional ML
Q 24.
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 25.
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
Q 26.
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 27.
_________ helps us to summarise all the key points into one single Template so that in future, whenever there is a need to look back at the basis of the problem, we can take a look at this and understand the key elements of it.
Problem Statement Template
4Ws Problem Canvas
Problem Scoping
AI Project Cycle
Q 28.
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 29.
Under _________, one looks at various parameters which affect the problem we wish to solve, as this would make many lives better.
Problem Scoping
Data Acquisition
Problem Statement Template
Data Exploration
Q 30.
The __________________canvas helps you in identifying the key elements related to the problem.
Problem Scoping
4Ws Problem
Project cycle
Algorithm
Q 31.
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 32.
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 33.
Identify the algorithm based on the given graph
Dimensionality reduction
Classification
Clustering
Regression