A team is training a computer vision model. They have a dataset of images with labels, but the images are of varying sizes. Which of the following steps is essential in the data preparation phase of the training workflow?

Resize all images to a fixed dimension and normalize pixel values.

Shuffle the dataset and split it into training and validation sets.

Convert all images to grayscale to reduce file size.

Increase the resolution of all images to the highest available quality.

After a trained sentiment analysis model outputs a probability of 0.85 for the 'positive' class, what does this output typically represent?

The exact accuracy of the model on the training set

The model's confidence that the input text is positive

The loss value from the last training epoch

The number of positive words in the input text

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Domain 1Objective 1

Demonstrate the Ability to Train and Inference CERTIFIED-AI-EXPERT Practice Questions (Page 6)

Part of the AI Overview domain, which accounts for 15% of the CERTIFIED-AI-EXPERT exam. NetApp does not publish an official question count, but from its 90-minute exam (~35–60 total, ~5–9 in this domain), expect 1–2 from this objective — we provide 27 practice questions to prepare you well beyond it. (estimate)

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Questions 26–27

26application · medium
A team is training a computer vision model. They have a dataset of images with labels, but the images are of varying sizes. Which of the following steps is essential in the data preparation phase of the training workflow?
Select an answer first
27foundation · easy
After a trained sentiment analysis model outputs a probability of 0.85 for the 'positive' class, what does this output typically represent?
Select an answer first

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Demonstrate the Ability to Train and Inference CERTIFIED-AI-EXPERT Practice Questions (Page 6)

Questions 26–27

A team is training a computer vision model. They have a dataset of images with labels, but the images are of varying sizes. Which of the following steps is essential in the data preparation phase of the training workflow?

After a trained sentiment analysis model outputs a probability of 0.85 for the 'positive' class, what does this output typically represent?

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