KNN Algorithm with notes and Video for explanation with examples.

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  1. Introduction.
  2. What is KNN?
  3. Video for better understanding.
  4. Notes on KNN.

The K-Nearest Neighbors (KNN) algorithm is a simple yet powerful classification and regression algorithm that is widely used in machine learning. It is a non-parametric algorithm that does not make any assumptions about the underlying data distribution. In this article, we will explore the KNN algorithm in detail and provide a step-by-step guide on how to implement it in Python.

What is the K-Nearest Neighbors (KNN) Algorithm?

The KNN algorithm is a type of instance-based learning, which means that it makes predictions based on the data instances or examples that are closest to a new data point. The KNN algorithm is called the K-Nearest Neighbors algorithm because it considers the K closest neighbors to the new data point when making a predictions the average of the K nearest neighbors’ target values as the predicted value for the new data point.

A Video for better understanding on what is KNN algorithm.


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