Machine Learning
A subset of AI that enables systems to learn and improve from experience.
Definition
Machine Learning (ML) is a subset of AI focused on building systems that learn from data to improve performance without explicit programming. ML algorithms identify patterns in data to make predictions or decisions. Applications include recommendation engines, fraud detection, image recognition, and predictive analytics. ML requires quality data and ongoing model training.
Why It Matters
Machine learning enables systems to improve from experience without explicit programming. It powers everything from spam filters to recommendation engines to fraud detection, finding patterns humans couldn't identify manually.
For businesses, ML offers the ability to extract value from data at scale. Understanding where ML applies—and where it doesn't—helps organizations invest in genuinely valuable applications.
Examples in Practice
An ML model predicts customer churn with 85% accuracy, enabling proactive retention efforts.
A fraud detection system catches suspicious transactions human reviewers would miss.
A demand forecasting model reduces inventory costs by 30% through better prediction.