Simple Nearest Neighbors Regression and Classification

Offered By
In this Guided Project, you will:

Formulate small examples of KNN classification by hand

Implement a KNN Classification algorithm in Python

Implement a KNN Regression algorithm in Python

2 hours
Intermediate
No download needed
Split-screen video
English
Desktop only

In this 2-hour long project-based course, we will explore the basic principles behind the K-Nearest Neighbors algorithm, as well as learn how to implement KNN for decision making in Python. A simple, easy-to-implement supervised machine learning algorithm that can be used to solve both classification and regression problems is the k-nearest neighbors (KNN) algorithm. The fundamental principle is that you enter a known data set, add an unknown data point, and the algorithm will tell you which class corresponds to that unknown data point. The unknown is characterized by a straightforward neighborly vote, where the "winner" class is the class of near neighbors. It is most commonly used for predictive decision-making. For instance,: Is a consumer going to default on a loan or not? Will the company make a profit? Should we extend into a certain sector of the market? Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

Skills you will develop

  • Statistical Analysis

  • Machine Learning

  • Python Programming

  • K-Nearest Neighbors Algorithm (K-NN)

  • Classification Algorithms

Learn step-by-step

In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:

  1. Understanding the Basic Structure of a KNN model

  2. Computing a simple KNN by hand

  3. Looking at an example of a KNN in action in Python

  4. Implementing an example KNN Regression in Python

  5. Implementing an example KNN Classification in Python

How Guided Projects work

Your workspace is a cloud desktop right in your browser, no download required

In a split-screen video, your instructor guides you step-by-step

Frequently asked questions

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Yes, everything you need to complete your Guided Project will be available in a cloud desktop that is available in your browser.

You'll learn by doing through completing tasks in a split-screen environment directly in your browser. On the left side of the screen, you'll complete the task in your workspace. On the right side of the screen, you'll watch an instructor walk you through the project, step-by-step.

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