2- Binary Classification Using Machine Learning | K-NN

In this video, we will understand and implement the K-Nearest Neighbor Algorithm which is a supervised, distance-based algorithm that uses Euclidean distance to calculate the distance between a given sample and each sample within the dataset. ** Code and Resources: ** - Preparing the dataset: https://www.youtube.com/watch?v=nVoGQKHt_rI&ab_channel=MachineMindscape - Code: https://github.com/anumfatima427/AI_projects_for_everyone/blob/main/1-binary-classfication-using-ml-algorithms.ipynb - Machine Learning for Beginners Course by FreeCodeCamp: https://www.youtube.com/watch?v=i_LwzRVP7bg&list=PLWKjhJtqVAblStefaz_YOVpDWqcRScc2s&ab_channel=freeCodeCamp.org ** Contents ** - 0:00 Intro - 0:24 dataset preparation recap - 0:54 K-NN Algorithm concept with examples - 6:33 K-NN code implementation - 9:10 outro 🔔 Subscribe: Don't miss out on future tutorials, tips, and insights! Subscribe to our channel and hit the notification bell to stay updated. 📌 Visit My Blog: For more tutorials, articles, and resources, visit my blog at https://machinemindscape.com/ 👍 Connect: Have questions or suggestions? Leave a comment below