A team is training a support vector machine (SVM) on a large dataset with millions of samples. Training is taking too long. They want to reduce training time while maintaining accuracy. Which structural modification is most appropriate?

Reduce the number of support vectors by using a smaller training set

Use a higher-degree polynomial kernel to capture more complex patterns

Increase the regularization parameter C to make the model simpler

Use a linear kernel instead of a non-linear kernel if the data is linearly separable

Which of the following is an example of optimizing an algorithm's structure to improve efficiency?

Using a larger batch size during gradient descent

Increasing the number of training epochs to allow the model to converge better

Replacing a recursive implementation with an iterative one to reduce function call overhead

Adding more training data to improve generalization

Which scenario is best suited for using grid search?

When the hyperparameter space is small and discrete

When the goal is to minimize the number of training runs

When hyperparameters are continuous and unbounded

When there are many hyperparameters with large ranges

How does random search select hyperparameter combinations?

It uses a surrogate model to predict promising regions

It tries every combination of a predefined set of values

It samples values from specified distributions for each hyperparameter

It starts with random values and then refines them using gradient descent

Certified Artificial Intelligence Practitioner (CAIP)

Domain 3Objective 2

Objective 3.2 Optimize the Algorithm (e.g., Structure, Run Time, Tuning Hyperparameters) AIP-210 Practice Questions (Page 2)

Part of the 3.0 Training and Tuning ML Systems and Models domain, which accounts for 24% of the AIP-210 exam.

30questions here

6free pages

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24%of the exam

Questions 6–10

6application · medium
A team is training a support vector machine (SVM) on a large dataset with millions of samples. Training is taking too long. They want to reduce training time while maintaining accuracy. Which structural modification is most appropriate?
Select an answer first
7foundation · easy
Which of the following is an example of optimizing an algorithm's structure to improve efficiency?
Select an answer first
8foundation · easy
Which scenario is best suited for using grid search?
Select an answer first
9application · medium
A team is using Optuna to tune a model. They want to stop unpromising trials early to save compute time. Which Optuna feature should they use?
Select an answer first
10foundation · easy
How does random search select hyperparameter combinations?
Select an answer first

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