Explore the power of k-nearest neighbors (kNN) in this deep dive into machine learning techniques for both classification and regression. Learn how to calculate distances with metrics like Euclidean distance, and understand when to use kNN for predictive modeling. We implement kNN using Python with scikit-learn, showing you how to select the optimal value of k and apply cross-validation. Perfect for students or professionals in data science looking to enhance their toolkit with practical examples in supervised learning.
