Machine Learning: Computers Teach Themselves Complex Tasks by Finding Patterns in Data
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Machine learning allows computers to perform tasks traditionally requiring human intelligence by learning from data instead of explicit programming.
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There are 4 main types of machine learning supervised (learning from labeled examples), unsupervised (finding patterns in unlabeled data), semi-supervised (combining labeled and unlabeled data), and reinforcement learning (learning by trial-and-error through rewards and penalties).
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Machine learning has many practical applications, like creating mood-based playlists by analyzing songs' musical qualities or improving websites by detecting user behavior patterns.
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Quantum computing has the potential to drastically enhance machine learning in the future by massively increasing processing power.
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Machine learning involves training algorithms on datasets to discern complex relationships and make predictions, rather than directly programming decision-making criteria.