MISSION 139

Introduction To K-Nearest Neighbors

Learn the basics of machine learning to suggest optimal AirBnB list prices.

Objectives

  • The basics of the machine learning workflow.
  • How the k-nearest neighbors algorithm works.
  • The role of Euclidean distance in machine learning.

Mission Outline

1. Problem definition
2. Introduction to the data
3. K-nearest neighbors
4. Euclidean distance
5. Calculate distance for all observations
6. Randomizing, and sorting
7. Average price
8. Function to make predictions
9. Next steps
10. Takeaways

machine-learning-fundamentals

Course Info:

Machine Learning Fundamentals

Beginner

The median completion time for this course is 7 hours.

This course requires a premium subscription. This course includes five missions and one guided project.  It is the 17th course in the Data Scientist in Python path.

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