MISSION 30

An Introduction to K-Nearest Neighbors

Use the kNN algorithm to identify the NBA player who's the most similar to Lebron James.

Objectives

  • Lean how to implement the K-Nearest Neighbors algorithm.
  • Learn how to make a prediction using the KNN algorithm.

Mission Outline

1. Introduction to the Data
2. Understanding the kNN Algorithm
3. Finding Similar Rows With Euclidean Distance
4. Normalizing Columns
5. Finding the Nearest Neighbor
6. Generating Training and Testing Sets
7. Using sklearn
8. Computing Error

Course Info:

Exploring Topics in Data Science

Intermediate

The average completion time for this course is 10-hours.

This course requires a premium subscription and includes two paid missions  It is the 29th course in the Data Scientist In Python path.

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