Final thoughts on K Nearest Neighbors 
Final thoughts on K Nearest Neighbors
by Harrison Kinsley
Video Lecture 19 of 42
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Date Added: August 11, 2016

Lecture Description

We're going to cover a few final thoughts on the K Nearest Neighbors algorithm here, including the value for K, confidence, speed, and the pros and cons of the algorithm now that we understand more about how it works.

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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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