Supervised learning uses structured, labeled data to train models, allowing a clear understanding of relationships between inputs and outputs, which suits classification and regression tasks.
Unsupervised learning differs as it works with unlabeled data, discovering patterns or groupings within datasets without predefined labels, making it useful for clustering and anomaly detection.
#machine-learning #supervised-learning #unsupervised-learning #data-driven-decisions #ai-implementation
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