Understanding Supervised and Unsupervised Learning
Supervised vs Unsupervised Learning: Supervised learning involves training AI models on labeled datasets, making it suitable for tasks like object recognition or fraud detection. In contrast, unsupervised learning uses unlabeled data to uncover patterns or groupings, such as clustering customers based on behavior. Supervised learning delivers targeted results, while unsupervised learning is exploratory, offering insights into unknown data structures. Both methods are foundational to machine learning, enabling solutions across diverse industries.
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