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The global unsupervised learning market is estimated to reach $86.1 billion by 2032, witnessing a CAGR of 35.7% from 2023 to 2032. This growth is attributed to the rise in availability of huge and diverse datasets and advancements in artificial intelligence and machine learning techniques. Unsupervised learning is a branch of artificial intelligence that involves the training of an algorithm on unstructured data. The goal of unsupervised learning is to detect hidden insights within the data, such as clusters or representations. It is commonly used in tasks such as data cluster, dimensional accuracy, anomaly detection, and synthetic data generation.
