What is the best way to design an algorithm for unsupervised learning in AI?
Unsupervised learning is a branch of artificial intelligence (AI) that deals with finding patterns and structures in data without any labels or guidance. Unlike supervised learning, where the algorithm learns from predefined examples and feedback, unsupervised learning explores the data on its own and discovers hidden features and relationships. This can be useful for tasks such as clustering, anomaly detection, dimensionality reduction, and generative modeling. But how do you design an algorithm for unsupervised learning in AI? Here are some tips and best practices to consider.
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