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

exploring-topics

Course Info:

Exploring Topics in Data Science

Intermediate

The median completion time for this course is 6.09 hours.

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

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