
AIProjLfCyclCBSEGrade10
Authored by Sunita Kumar
Computers
9th - 10th Grade
Used 25+ times

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15 questions
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1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Name the phase which comes before data exploration. In this phase data needed for an AI project is collected through various sources and generally in different formats.
Modelling
Problem Scoping
Evaluation
Data Acquisition
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
In which phase of an AI project life cycle, the right algorithms are selected and an AI model for working with the data is built. The selection of the model depends upon the data being used and outcome desired.
Modelling
Problem Scoping
Data Exploration
None of the above.
3.
MULTIPLE CHOICE QUESTION
20 sec • 1 pt
Which of the following tool is used in problem scoping phase of an AI project life cycle?
Classification
Clustering
4Ws problem Canvas
None of the above.
4.
MULTIPLE SELECT QUESTION
45 sec • 3 pts
Which are the correct options for rule based AI models?
Machine Learning is static as no change in original dataset can be made by machine itself.
It is used to develop simple AI projects.
It is used to develop complex AI projects.
Rules are defined by developer.
5.
MULTIPLE SELECT QUESTION
20 sec • 2 pts
4 Ws Problem Canvas asks four questions. These are :
When
What
Which
Where
6.
MULTIPLE SELECT QUESTION
30 sec • 3 pts
An AI model is a program or algorithm that utilizes a set of data that enables it to recognize found data patterns. This allows it to reach a conclusion or make a prediction when provided with sufficient information. Types of AI models are :
4Ws Problem Canvas
Classification
Regression
Clustering
7.
MULTIPLE SELECT QUESTION
1 min • 5 pts
Which of the following statements are true ?
Dataset used in evaluation phase for ML model is called testing dataset. It is the final step to verify ML Model's functionality.
Dataset used in modelling phase to train the ML model is called training dataset. It consists of 70% of dataset set aside in Data acquisition phase.
Dataset used in modelling phase to check the output of developed ML model is called validation dataset. It usually consists of 30% of dataset available in modelling phase.
Generally during data acquisition phase, 80% dataset is reserved for training plus validating ML model and just 20% for Evaluation phase.
Dataset used in in evaluation phase is new dataset which has never been seen by ML model.
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