SVM Algorithm with its types and terminologies with notes and Video for explanation

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

The Support Vector Machine (SVM) algorithm is a popular supervised machine learning algorithm that is widely used for classification and regression tasks. It is a powerful algorithm that is particularly useful when dealing with high-dimensional datasets. In this article, we will explore the SVM algorithm in detail and provide a step-by-step guide on how to implement it in Python.

What is the Support Vector Machine (SVM) Algorithm?

The SVM algorithm is a binary classification algorithm that works by finding the hyperplane that best separates the data points of different classes. The hyperplane is chosen such that the margin between the hyperplane and the closest data points of each class is maximized. The closest data points to the hyperplane are called support vectors, hence the name Support Vector Machine.

A Video for better understanding on what is SVM algorithm.


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