<ul data-eligibleForWebStory="true"><li>Machine learning algorithms make AI applications like fraud detection and forecasting sales feasible.</li><li>Supervised learning uses labeled data for predictions, while unsupervised finds hidden patterns.</li><li>Supervised learning suits clear outcomes like predictions, while unsupervised is for data exploration.</li><li>Examples include fraud detection in finance for supervised and customer segmentation in marketing for unsupervised.</li></ul>

Supervised vs Unsupervised Learning: Key Differences & Examples

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