Machine Learning: K-Nearest Neighbors

Overview

Implement and assess the K-Nearest Neighbors algorithm.

Continue your Machine Learning journey with Machine Learning: K-Nearest Neighbors (KNN). Learn how to classify unknown data points based on their similarity to other, known, data points. Use distance and proximity to validate your predictions, and get started with classification techniques.

* Prepare data for a KNN model

* Explain distance and proximity

* Implement and assess a KNN model

Syllabus

Classification: K-Nearest Neighbors: K-Nearest Neighbors is a supervised machine learning algorithm for classification. You will implement and test this algorithm on several datasets.

Lesson: Distance Formula
Article: Normalization
Article: Training Set vs Validation Set vs Test Set
Lesson: K-Nearest Neighbors
Quiz: K-Nearest Neighbors
Project: Cancer Classifier
Informational: Next Steps