Lecture 3.4 | KNN Algorithm In Machine Learning | K Nearest Neighbor | Classification |
Welcome to our comprehensive tutorial on the K-Nearest Neighbors (KNN) Algorithm! In this in-depth YouTube video, we provide a step-by-step guide to mastering the KNN Algorithm, covering its concepts, distance metrics, hyperparameter tuning, and practical applications.
The K-Nearest Neighbors (KNN) Algorithm is a versatile and intuitive machine learning algorithm used for both classification and regression tasks. It makes predictions by considering the K nearest neighbors to an unlabeled data point, based on their proximity in the feature space.
In this tutorial, we delve into the following key aspects of the KNN Algorithm:
1. Introduction to the KNN Algorithm
2. Distance Metrics
3. Choosing the Value of K
4. Example with dataset
By the end of this tutorial, you will have a comprehensive understanding of the K-Nearest Neighbors (KNN) Algorithm, distance metrics, hyperparameter tuning, and how to apply this algorithm to various machine learning tasks.
Hashtags:
#KNNAlgorithm #MachineLearning #Classification #Regression #DistanceMetrics #HyperparameterTuning #DataScience #AI #Tutorial #YouTubeSEO #YouTubeTutorial #machinelearningtechniques #aktu #aktuexam #exam
