This video about “KNN Algorithm in Machine Learning” is a part of the Scikit-Learn Tutorial. You will learn what KNN Algorithm is, how it works and how it can be implemented in Scikit-Learn. So, without much further ado, let’s hop on into the video!!

What is KNN Algorithm?
KNN Algorithm or the K Nearest Neighbor algorithm is classified under Supervised Learning and is extensively used for classification and regression. It is a versatile algorithm that may also be used to impute missing values and resample datasets. As the name implies, it uses K Nearest Neighbors (Data points) to forecast the class or continuous value for the new Datapoint. KNN Algorithm is lazy and instance-based learning which is nonparametric.

Following Topics are covered in this session:
00:00 - What is K-Nearest Neighbor Algorithm?
6:03 - How to choose K Value?
8:50 - When Do We Choose KNN?
10:08 - How Does KNN Algorithm Work?
13:04 - Hands-on Demo

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