Machine Learning (ML)

Machine learning is a subfield of artificial intelligence in which systems learn to perform tasks by identifying patterns in data, rather than through explicit rule-based programming. ML algorithms are trained on labeled or unlabeled datasets to build models that can make predictions, classifications, or decisions on new, unseen inputs. Major paradigms include supervised learning, unsupervised learning, and reinforcement learning.

Machine learning is foundational to modern commerce technology. Recommendation engines, demand forecasting, fraud detection, dynamic pricing, and search ranking are all ML-driven systems in widespread production use. Unlike traditional software, ML models require ongoing data curation, retraining, and monitoring to remain accurate as user behavior and market conditions evolve. The operational discipline of managing ML systems in production — often called MLOps — is as important as the modeling itself in enterprise contexts.