A Step-by-Step Guide to K-Nearest Neighbors (KNN) in Machine Learning

Introduction Welcome back, everyone, to the 3rd blog post in our Machine Learning Algorithms Series! Today, we'll dive into K-Nearest Neighbors (KNN), a fundamental algorithm in machine learning. We'll be implementing the KNN algorithm from scratch in Python. By the end of this blog, you'll have a clear understanding of how KNN works, how to implement it, and when to use it. Let's get started! What is KNN? K-Nearest Neighbors (KNN) is a straightforward powerful supervised machine learning algorithm used for both classification and regression tasks. Its simplicity lies in its non-parametric nature, meaning it doesn't assume anything about the underlying data distribution. Instead, KNN works by finding the 'k' closest data points (neighbors) in the training dataset to a new input point and making predictions based on these neighbors. For classification tasks, KNN predicts the class label of the new data point by a majority vote among its nearest neighbors. The class label that appears mo