Yes, deep learning algorithms automatically extract features from data, which is one of their key advantages. Unlike traditional machine learning, where feature extraction is manual, deep learning models learn hierarchical features directly from raw data.
For example, convolutional neural networks (CNNs) automatically learn to detect edges, textures, and shapes in the initial layers, progressing to more complex patterns like objects or scenes in deeper layers. This capability eliminates the need for hand-crafted features.
This automation simplifies workflows and often results in better performance, as the features learned by deep learning models are optimized for the task at hand, such as image classification or object detection.