Deep learning is a subset of AI. It uses artificial neural networks that help digital systems to learn and make decisions based on unstructured, unlabeled data.

Deep learning is a subset of machine learning. The primary difference between the two is how each algorithm learns and how much data each type of algorithm requires. Since deep learning uses more data, enterprises generally rely on it for more complex tasks.

AI, machine learning, and deep learning are often used interchangeably. However, it’s easiest to think of these three as a series of AI systems from largest to smallest, each encompassing the next. AI is the overarching system, machine learning is a subset of AI, and deep learning is a subset of machine learning.

Deep learning is used within a wide range of industries in a variety of ways. Digital assistants, for example, use deep learning to understand speech and respond appropriately to queries and commands.

Deep learning is important because it reveals insights from vast data sets in ways that weren’t possible before. Companies across retail, healthcare, transportation, manufacturing, and other sectors are investing in deep learning to drive innovation, uncover opportunities, and stay relevant.

Azure employs deep learning through a complex system of neural network architectures, high-performance GPUs, and large volumes of labeled data. These services empower developers who use Azure to create intelligent, cutting-edge, market-ready, and responsible applications.