Machine Learning From Scratch - K-Nearest Neighbors (KNN) FROM SCRATCH in Python

Learn how to implement the K-Nearest Neighbors (KNN) algorithm from scratch in Python using just math and NumPy (no machine learning libraries like Scikit-Learn). I’ll start by explaining the intuition and core math concepts behind KNN, including the euclidian distance and majority voting, and then walk through how to turn this into code. This is Episode 3 of my Machine Learning From Scratch series, where I’m building ML algorithms from the ground up, step-by-step to truly understand how they work under the hood. 📺 Watch the Playlist Here: https://www.youtube.com/playlist?list=PLh6JMkwECi5HXVJ58ue58jJvL599NFYja 📊 Kaggle Dataset: https://www.kaggle.com/datasets/uciml/breast-cancer-wisconsin-data 💻 Full Code on GitHub: https://github.com/harryconnor/Machine-Learning-From-Scratch TIMESTAMPS: 00:00 - Introduction 00:22 - PART 1: Intuition & Math 03:26 - PART 2: Coding it up #machinelearning #python