A company needs to develop an ML model. The model must identify an item in an image and must provide the location of the item. Which Amazon SageMaker algorithm will meet these requirements?

Question

Options

• AImage classification
• BXGBoost
• CObject detection
• DK-nearest neighbors (k-NN)

• A
  3% (1)
• B
  6% (2)
• C
  88% (29)
• D
  3% (1)

Explanation

Object detection (C) is correct because it does exactly two things the question requires: it identifies what an object is (classification) and where it is in the image (localization via bounding boxes) - both capabilities in a single algorithm.

Image classification (A) only labels the image as a whole ("this is a cat") but provides no location information, so it fails the "where is it" requirement. XGBoost (B) is a gradient-boosted tree algorithm designed for structured/tabular data, not image analysis. K-nearest neighbors (D) is a general-purpose distance-based algorithm used for classification or regression on feature vectors - it has no image-spatial awareness.

Memory tip: Think "detection = identification + location." The word detect implies finding something, which means knowing where it is - if the question mentions bounding boxes, coordinates, or locating an object, that's your signal to choose Object Detection over plain Image Classification.

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