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ii. Assertion (A): The AI project cycle provides the right framework to guide us to our goals.
Reason (R): AI project cycle is an iterative process.
Ans. b
iii. Assertion (A): Once a model has been created and trained, it can be deployed without evaluation.
Reason (R): The model can be evaluated using Testing Data and the model's efficiency can be assessed.
Ans. d
iv. Assertion (A): During “Exploratory Data Analysis”, the initial insights gained help to get an understanding of the
data and later on, help in algorithm selection, metrics choice, etc.
Reason (R): The quality of the data being used by the AI model does not affect the model.
Ans. c
v. Assertion (A): A separate validation dataset is used for evaluation during training.
Reason (R): The team involved in testing must develop test suites to aid in the validation of the ML models.
Ans. b
2. Which of the following statements is/are INCORRECT. [CBSE Sample Paper, 2022]
i) The volume of test data can be large, that presents complexities.
ii) Your testing team should test the AI and ML algorithms keeping model validation, successful learn ability, and
algorithm effectiveness in mind.
iii) Test data should include all irrelevant subsets of training data, i.e., the data you will use for training the AI
system.
a. None of the Below b. ii)
c. iii) d. i), ii) & iii)
Ans. c
Unsolved Questions
S CTI N A (Objective Type Questions)
uiz
A Tick ( ) the correct option
1. The block in the 4Ws problem canvas refers to the setting in which the stakeholders experience
this problem.
a. Who b. What
c. Where d. Why
2. Which of the following are the objectives of the testing team in AI modelling?
(i) Model Validation (ii) Security compliance
(iii) Accurate predictions (iv) Minimising bias
a. (i), (ii) and (iii) b. (ii), (iii) and (iv)
c. (i), (iii) and (iv) d. (i), (ii) and (iv)
3. For a balanced dataset, which of the following may be a useful choice for evaluating a classification model?
a. Design b. Accuracy
c. Evaluation d. Acquire
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