Machine Learning with K-Nearest Neighbors

with Hristina Hristova

Introducing you to the exciting topic of machine learning with the K-nearest neighbors algorithm using Python’s scikit-learn library.

1 hour 17 lessons
Start course

Course Overview

Practical knowledge of various machine learning algorithms is essential for machine learning enthusiasts and experts alike. In this course, we focus extensively on one of the most intuitive and easy-to-implement ML algorithms out there – K-nearest neighbors, or KNN for short. Step by step, we will first lay the foundations and expand your mathematical toolbox. Then, you will progress to coding and using Python’s scikit-learn library to solve a randomly generated classification problem. Finally, you will apply KNN to a couple of regression tasks. In other words – you will learn all the subtleties that should be considered when applying the KNN algorithm in your future practice.

17 High Quality Lessons
3 Practical Tasks
1 Hour of Video
Certificate of Achievement

Topics covered

machine learningMathematicsProgrammingPythonTheory

What You'll Learn

Aiming to upgrade your machine learning skills? This course will help you:

Get acquainted with different distance metrics
Grasp the working of the KNN algorithm
Generate random datasets
Use scikit-learn’s KNN algorithms
Construct decision boundaries
Understand the pros and cons of the KNN algorithm


Student feedback


314 ratings
5 stars
269 (86%)
4 stars
35 (11%)
3 stars
8 (3%)
2 stars
2 (1%)
1 star
0 (0%)
Filter by rating
  • 5 stars
  • 4 stars
  • 3 stars
  • 2 stars
  • 1 stars
  • Newest
  • Oldest
This course has amazing visualizations while teaching, that I have never seen like this before! This is one of the very exciting experiences I ever had. I hope every other course of "365datascience" would be like this...!
I love the explanations with the real world examples. It makes everything easier to understand. The course is good for beginners and gives a solid foundation and understanding of KNN.
THis instructor is one of the best you can meet, but actually she did the Naive Bayes course better than this But still Highly recommended
A valuable and interesting course. Examples presented were helpful in understanding the KNN Classifier, Regressor and Algorithm.
The course is such amazing and well structured. Awesome work done.
  • 1
  • 2
  • 3
  • ...
  • 5
  • ...
  • 9

“KNN is an essential step in the development of every machine learning practitioner. It serves as a perfect example of a rather simple algorithm performing incredibly well and allowing for diverse practical applications. Moreover, it is great fun to visually compare the results from different KNN models on the same dataset.”

Hristina Hristova
Content Creator at 365 Data Science
Machine Learning with K-Nearest Neighbors

with Hristina Hristova

Start Course