K-Means clustering: think of it as organizing a room full of strangers into smaller friend groups based on shared interests. Similarly, K-Means groups data points based on their similarities. In finance, this helps in classifying customers, investments, or market trends. By uncovering hidden patterns, K-Means offers valuable insights, guiding better decisions in portfolio management and customer service. A handy tool for making sense of vast data!
In finance, Supervised Machine Learning is like teaching a computer with a guide. You provide specific examples with correct answers, and it learns patterns for future predictions. It's a matching game with clear outcomes. Conversely, Unsupervised Machine Learning lets the computer explore data independently, finding hidden patterns or groupings. Think of giving a computer financial indicators without outcomes; it uncovers