Unsupervised Learning

Unsupervised learning is a machine learning paradigm where algorithms learn patterns and structures from unlabeled data without explicit supervision or predefined targets. It includes techniques such as clustering, dimensionality reduction, and anomaly detection for discovering hidden patterns and relationships in data. Readers can explore how unsupervised learning algorithms enable data exploration, pattern recognition, and knowledge discovery in diverse domains, such as customer segmentation, anomaly detection, and data preprocessing in machine learning pipelines.

Comprehensive roadmap for unsupervised-learning

By roadmap.sh