AIProjLfCyclCBSEGrade10

AIProjLfCyclCBSEGrade10

9th - 10th Grade

15 Qs

quiz-placeholder

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AIProjLfCyclCBSEGrade10

AIProjLfCyclCBSEGrade10

Assessment

Quiz

Computers

9th - 10th Grade

Practice Problem

Hard

Created by

Sunita Kumar

Used 25+ times

FREE Resource

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15 questions

Show all answers

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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