K-Nearest Neighbors (KNN)

Learn about K-Nearest Neighbors (KNN), a simple yet effective algorithm used for both classification and regression. Understand how KNN makes predictions based on the proximity of data points, and explore real-world use cases in recommendation systems and pattern recognition. Practice KNN implementations in Python using scikit-learn.

Introduction

Get introduced to K-Nearest Neighbors (KNN), a simple yet powerful algorithm for classification and regression.

Theory

Understand the theory behind KNN, focusing on distance metrics and decision boundaries.

scikit-learn Example

Use scikit-learn to easily implement and evaluate KNN models.

TensorFlow Example

Implement the KNN algorithm using TensorFlow with practical examples.

PyTorch Example

Learn how to build KNN models in PyTorch for both classification and regression.

Common Mistakes & Best Practices

Avoid common mistakes in KNN and follow best practices to improve your models.

Comparison with Other Algorithms

Compare KNN with other algorithms to understand its applications and limitations.