H13-311_V3.5 · Question #307
Deep learning algorithms can be divided into supervised learning and unsupervised learning.
The correct answer is A. True. Option A is correct because deep learning, as a subset of machine learning, inherits the same fundamental learning paradigms: supervised learning (where models train on labeled data, e.g., CNNs for image classification) and unsupervised learning (where models find patterns in…
Question
Deep learning algorithms can be divided into supervised learning and unsupervised learning.
Options
- ATrue
- BFalse
How the community answered
(37 responses)- A78% (29)
- B22% (8)
Explanation
Option A is correct because deep learning, as a subset of machine learning, inherits the same fundamental learning paradigms: supervised learning (where models train on labeled data, e.g., CNNs for image classification) and unsupervised learning (where models find patterns in unlabeled data, e.g., autoencoders and GANs). This division applies directly to deep learning architectures and training strategies, not just traditional ML methods. Option B is wrong because it would imply deep learning operates outside these established categories, which contradicts how deep learning models are actually trained and classified in practice.
Memory tip: Think of deep learning as a specialization of machine learning - it inherits the supervised/unsupervised split but uses neural networks with many layers to do the heavy lifting. If ML has it, deep learning has it too.
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