What Is Machine Learning? Definition, Examples & Use Cases
What Is Machine Learning? Machine learning (ML) lets systems identify patterns and make predictions—whether it’s sorting images, forecasting demand, or tailoring user experiences. By training statistical models on large datasets and letting them learn autonomously, ML continually improves over time. To see how this plays out across an entire organization, you can dive into the AI Business Automation: Boost Efficiency & Drive Growth pillar. A Brief History The Early Days (1950s–1970s) Early perceptron experiments laid the foundation for today’s predictive insights in the business intelligence toolkit . Statistical Learning Era (1980s–1990s) Techniques like decision trees and support vector machines unlocked robust classification and regression—core to modern accounting automation playbook . Big Data & Kernel Methods (2000s) As data volumes exploded, kernel-based methods (SVMs, Gaussian processes) became go-to tools for spotting anomalies in threat detection strateg...