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Unsupervised Learning
Unsupervised learning is a type of machine learning where the algorithm learns patterns from data without explicit human intervention or labels. It aims to discover hidden structures, groupings, or relationships within the input data itself. Unlike supervised learning, there's no 'correct' output provided for the algorithm to learn from.
In plain terms
Imagine giving an alien thousands of photos and asking it to group them based on what it sees, without telling it what a 'cat' or 'dog' is.
Why it matters
It's crucial for mining insights from vast amounts of unlabeled data, which is plentiful and often expensive to label manually.
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