Self-Organizing Maps (SOMs) are used in deep learning for data mining.
SOMs excel at clustering high-dimensional data and can be used for tasks like customer segmentation and market basket analysis.
SOMs reduce the dimensionality of complex data while preserving important features, making visualization and analysis easier.
SOMs are useful for creating intuitive visualizations, detecting anomalies, but require careful selection of parameters and can be sensitive to weight initialization.