This paper presents a comparative study of supervised and unsupervised learning techniques and their applicability to real-world problems. It outlines the key concepts, methodologies, strengths, and limitations of each approach, while also highlighting practical applications across domains such as healthcare, finance, and natural language processing.
Supervised learning, Unsupervised learning techniques, Machine Learning, real world applications