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Machine Learning (ML) is a subset of Artificial Intelligence (AI) that enables systems to automatically learn and improve from experience without being explicitly programmed. It involves training algorithms to make decisions or predictions based on data. Machine Learning combines data, algorithms, and computational power to create models that uncover patterns and make accurate forecasts or decisions.
What is the difference between supervised and unsupervised learning?
Supervised learning uses labeled data to train models, while unsupervised learning works with unlabeled data to find patterns.
How does Machine Learning differ from traditional programming?
In traditional programming, rules are explicitly defined, but in ML, models learn patterns from data to make decisions.
What industries widely use Machine Learning?
ML is widely applied in healthcare, finance, e-commerce, marketing, and autonomous vehicles, among others.