Demystifying K-Nearest Neighbors: A Beginner’s Guide in Python

A Gentle Introduction to the KNN Algorithm for Newcomers to Machine Learning

In this article, we embark on a journey to demystify KNN, the algorithm that makes predictions based on the company it keeps, quite literally. We will explore how KNN takes inspiration from our everyday experiences, where we often seek advice from our nearest neighbors, friends, or colleagues.

We will dive into two key aspects of KNN: classification and regression. In the world of classification, KNN helps us assign labels or categories to new data points based on their resemblance to previously observed instances. It is a vital tool in tasks like spam detection, image recognition, and disease diagnosis. In the task of regression, KNN enables us to predict continuous values, making it indispensable for applications such as real estate price prediction, stock market forecasting, and more.

Intuition of the KNN Algorithm

K-Nearest Neighbors (KNN) is a simple and intuitive machine learning algorithm used for both classification and regression tasks. But first, what does classification and regression mean?

• Classification is a type of supervised learning where the goal is to categorize data points…