A subset of AI that enables systems to automatically learn and improve from experience without being explicitly programmed. ML algorithms build models based on training data to make predictions or decisions.
A field of computer science focused on creating systems that can perform tasks typically requiring human intelligence. This includes learning from experience, understanding language, recognizing patterns, solving problems, and making decisions.
A machine learning approach where the model is trained on labelled input-output pairs. The model learns to map inputs to correct outputs, enabling predictions on new, unseen data. Most commercial ML models in production today are supervised.
A machine learning approach that discovers structure in unlabelled data. Common techniques include clustering (grouping similar items) and dimensionality reduction. It is often used for anomaly detection and exploratory data analysis.
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