Writing our own K Nearest Neighbors in Code 
Writing our own K Nearest Neighbors in Code
by Harrison Kinsley
Video Lecture 17 of 42
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Date Added: August 11, 2016

Lecture Description

In the previous tutorial, we began structuring our K Nearest Neighbors example, and here we're going to finish it. The idea of K nearest neighbors is to just take a "vote" of the closest known data featuresets. Whichever class is closest overall, is the class we assign to the unknown data.


Course Index

Course Description

The objective of this course is to give you a holistic understanding of machine learning, covering theory, application, and inner workings of supervised, unsupervised, and deep learning algorithms.

In this series, we'll be covering linear regression, K Nearest Neighbors, Support Vector Machines (SVM), flat clustering, hierarchical clustering, and neural networks.


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