A company needs to train an ML model to classify images of different types of animals. The company has a large dataset of labeled images and will not label more data. Which type of learning should…

The correct answer is A. Supervised learning. Supervised learning is appropriate when the dataset is labeled. The model uses this data to learn patterns and classify images. Unsupervised learning, reinforcement learning, and active learning are not suitable since they either require unlabeled data or different problem…

Submitted by lars.no· Mar 30, 2026

Question

A company needs to train an ML model to classify images of different types of animals. The company has a large dataset of labeled images and will not label more data. Which type of learning should the company use to train the model?

Options

ASupervised learning.
BUnsupervised learning.
CReinforcement learning.
DActive learning.

How the community answered

(26 responses)

A
77% (20)
B
4% (1)
C
8% (2)
D
12% (3)

Explanation

Supervised learning is appropriate when the dataset is labeled. The model uses this data to learn patterns and classify images. Unsupervised learning, reinforcement learning, and active learning are not suitable since they either require unlabeled data or different problem settings.

Topics

#Supervised learning#Image classification#Labeled datasets

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