Machine learning: definition

Machine learning is a branch of AI where a system learns patterns from data and improves at a task through examples, instead of being programmed with explicit rules.

Instead of a developer writing every rule, you show the system thousands of examples and it learns the pattern. That is machine learning, and it underpins everything from spam filters to recommendations to the large models behind generative AI.

The practical takeaway is that an ML system is only as good as the data it learns from. Clean, representative data makes it useful; biased or messy data bakes those problems in.

Related terms

Deep learning: Deep learning is machine learning that uses many-layered neural networks to learn complex patterns, and it is the approach behind most modern AI breakthroughs.
Neural network: A neural network is a computing system loosely inspired by the brain, made of layers of connected nodes that adjust their strengths as they learn from data.
Model training: Model training is the process of teaching an AI model by showing it data and adjusting its internal parameters until it performs the task well, which is done once up front and is computationally expensive.