Deep learning is a specialized branch of machine learning that trains computer systems using multi-layered artificial neural networks modeled loosely after the human brain. What sets it apart from traditional computer science is its ability to automatically discover patterns and extract relevant features from massive amounts of unstructured data (like raw video, audio, or text) without explicit human programming or manual intervention. The AI Hierarchy
To understand where deep learning fits, it helps to look at the hierarchy of modern computer intelligence:
Artificial Intelligence (AI): The broad umbrella covering any software or machine that mimics human intelligence.
Machine Learning (ML): A subset of AI where systems use statistical algorithms to learn patterns directly from data.
Deep Learning (DL): A specialized subset of machine learning focused specifically on neural networks with many “hidden” layers.
┌───────────────────────────────────────────┐ │ Artificial Intelligence (AI) │ │ ┌─────────────────────────────────────┐ │ │ │ Machine Learning (ML) │ │ │ │ ┌───────────────────────────────┐ │ │ │ │ │ Deep Learning (DL) │ │ │ │ │ └───────────────────────────────┘ │ │ │ └─────────────────────────────────────┘ │ └───────────────────────────────────────────┘ How It Works: The Layered Network
Deep learning networks are built out of thousands or millions of interconnected nodes called artificial neurons. The process operates through a continuous hierarchy: What Is Deep Learning? | IBM
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