In this in-depth KZitem video, we provide a thorough explanation of SVM, covering its various aspects, including types, kernels, hyperplanes, properties, and common issues.
Support Vector Machine is a powerful machine learning algorithm used for classification and regression tasks. It finds the optimal hyperplane that maximally separates data points of different classes, making it a versatile and widely-used tool in the field of data science.
we delve into the following topics:
Chapters :
00:00 - Introduction to Support Vector Machine
03:36 - Diagramatic explaination of SVM
06:10 - How svm works
06:50 - Types of Support Vector Machine
10:13 - What is Kernel
13:25 - Types of SVM kernels
18:02 - Hyperplane & Decision surface
19:50 - Properties of SVM
22:46 - Common Issues in support vector machine
By the end of this tutorial, you will have a comprehensive understanding of Support Vector Machine, its types, kernel functions, hyperplanes, properties, and how to tackle common issues.
Make sure to subscribe to our channel for more insightful tutorials on machine learning algorithms, hit the notification bell to stay updated with our latest videos, and feel free to leave your questions or comments below. Let's explore the world of Support Vector Machine together!
Hashtags:
#SupportVectorMachine #SVM #MachineLearning #ClassificationAlgorithm #machinelearningtechniques #DataScience #artificialintelligence #kernel #KernelFunctions #Hyperplane #Margin #Overfitting #Algorithm #Tutorial #KZitemTutorial #supervisedlearning #issues #ai #ml #mlt #properties
Негізгі бет Lecture 2.6 | Support Vector Machine (SVM) | Complete Explanation, Types, Kernels, Hyperplane #mlt
Пікірлер: 17