CS480-680 - K-Nearest Neighbours

Explore the fundamentals of machine learning with a focus on k-nearest neighbours in this comprehensive lecture. Delve into classification and regression techniques, examining real-world examples to understand their applications. Learn about consistent hypotheses and the concept of nearest neighbour algorithms. Discover how to implement and evaluate k-nearest neighbour models, including accuracy assessment and addressing underfitting issues. Gain valuable insights into this essential machine learning technique and its practical implications in data analysis and prediction tasks.

Intro
Recap
Classification and Regression
Classification Example
Classification Examples
Classification vs Regression
Machine Learning
Consistent Hypothesis
Nearest Neighbour
Knearest Neighbour
Accuracy
Underfitting