H13-321_V2.5 Exam Dumps : HCIP - AI EI Developer V2.5 Exam

In themulti-head attentionmechanism:

A:True — the input embedding dimension is split across multiple heads, so each head operates on a lower-dimensional subspace before concatenation.

B:True — having multiple attention heads allows the model to attend to information from different representation subspaces simultaneously.

C:False — each head has its own learned linear transformations for queries, keys, and values.

D:False — after concatenation, the result is passed through a final linear projection, not fed back into the attention module directly.

Exact Extract from HCIP-AI EI Developer V2.5:

"Multi-head attention divides the embedding dimension across heads to learn from multiple subspaces in parallel, then concatenates and linearly projects the result."

In NLP:

Text classification(e.g., sentiment analysis) predicts a single label for the entire input sequence.

Sequence labeling(e.g., Named Entity Recognition, Part-of-Speech tagging) produces an output label for each token or position in the input sequence.This distinction is important for selecting appropriate model architectures and loss functions.

Exact Extract from HCIP-AI EI Developer V2.5:

"Text classification assigns one label to the whole text, whereas sequence labeling assigns a label to each token in the sequence."

Gamma correction is anon-linearimage processing method used to adjust brightness and contrast. It is not limited to grayscale images — it can be applied to both grayscale and color images by operating on individual channels.

γ < 1:Enhances dark regions (brightens shadows) and compresses highlights.

γ > 1:Enhances bright regions and compresses dark regions.It is based onpower-law (exponential) transformation, making it effective for adjusting human-perceived luminance.

Exact Extract from HCIP-AI EI Developer V2.5:

"Gamma correction is a non-linear brightness adjustment based on power-law transformation. It applies to both grayscale and color images. For γ<1, dark regions are brightened; for γ>1, bright regions are enhanced."