Machine Learning revolves around Classification Problems, where the goal is to categorize things accurately. The more precise a model is at classifying, the better it can predict outcomes. Today, we’re fortunate to have Khun Golf Mathee Prasertkijaphan, a Data Analytics expert from SCB TechX, explain how we can use a method called K-Nearest Neighbors (KNN) to solve these classification problems. If you’re curious to learn more, just click for quick insights in just 1 minute.

K-Nearest Neighbors (KNN) is a handy tool for sorting things into groups, like identifying cancer cells. It works by comparing cells and grouping similar ones together. What’s cool is that it doesn’t need a bunch of training data; it uses what’s already there. This method is great for tricky datasets that need precise sorting. Plus, it gives us valuable info to help make smart decisions, especially in fields like medicine where choosing the right treatment is crucial.