What does deep learning mainly focus on?

Deep learning primarily focuses on training artificial neural networks that possess multiple layers, also known as deep neural networks. This characteristic allows deep learning models to automatically learn and extract hierarchical features from raw data, effectively capturing complex patterns. The architecture of these networks enables them to perform exceptionally well on various tasks such as image recognition, natural language processing, and more, by leveraging large amounts of unstructured data.

While labeled data for classification tasks, analyzing customer purchase patterns, and detecting fraudulent transactions can all involve machine learning methods, they do not encapsulate the essence of deep learning itself. Instead, these tasks can be addressed through various algorithms and techniques, whereas deep learning's defining aspect lies in the depth of the neural networks utilized, allowing for greater learning capacity and accuracy in complex scenarios.