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Unsupervised learning identifies patterns in data without predefined labels from "summary" of Machine Learning For Dummies by John Paul Mueller,Luca Massaron
Unsupervised learning is a powerful machine learning technique that allows algorithms to identify patterns in data without the need for predefined labels. This means that the algorithm is given a set of data and is tasked with finding hidden structures or relationships within it on its own. By doing so, unsupervised learning can uncover valuable insights and trends that may not be immediately apparent to human observers. One common application of unsupervised learning is clustering, where the algorithm groups similar data points together based on certain characteristics or features. This can help in segmenting data into meaningful categories or clusters, which can then be used for further analysis or decision-making. Another popular use case is dimensionality reduction, where the algorithm simplifies complex data by reducing the number of variables or features while retaining as much relevant informati...
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