Unsupervised Learning
Unsupervised learning is a type of machine learning where the algorithm tries to find patterns and hidden structures in data without any specific target output or labels. It's like giving a child a box of assorted toys and letting them sort them into groups that make sense to them, without telling them how to sort. Common tasks include clustering, where similar data points are grouped together, and dimensionality reduction, which simplifies complex data.
It's like finding natural groupings in a collection of unlabeled photos, such as separating pictures of animals from pictures of landscapes, without being told what any photo depicts.
It's crucial for understanding intrinsic data structures, detecting anomalies, and preparing data for other machine learning tasks when labeled data is scarce or expensive to obtain.
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