AWS Certified AI Practitioner AIF-C01 Practice Question

Deep learning models are built from neural networks that contain many hidden layers. Because the model learns hierarchical representations at each layer, practitioners do not have to hand-craft most features; instead, the network automatically extracts increasingly abstract features from raw data during training. The other statements describe decision-tree methods that still depend on manual feature engineering, unsupervised clustering techniques, or rule-based expert systems-none of which capture the defining multilayer representation learning that characterizes deep learning.