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.

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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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