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.

2 hours 17 lessons
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17 High Quality Lessons
3 Practical Tasks
2 Hours of Content
Certificate of Achievement

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.

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


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This instructor was Exceptional!!! She has a very good understanding of the material and is blessed to with the gift of explaining the material in such a way that allows you to learn and understand. Her teaching methods are spot on and she explains everything in a clear concise manner. Thank You.
Although ı am new in data journey, this course is exciting and comprehensive. Not only it has basic and fundamental content but also the tutor is great. İ cannot pass without saying that interactive and effective visuals help me to understand bettter. Thank you 👏
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...!
This course is particularly beneficial for individuals with prior knowledge of K-nearest neighbors (KNN). However, it remains a valuable resource for learners at all levels, offering substantial content and insights.
Lots of practical examples, just the way I like it. Really like these fast machine learning courses that first give you enough theoretical understanding and then goes straight into coding
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Hristina Hristova

“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