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This Support Vector Machine (SVM) tutorial video will help you understand the basics of the Support Vector Machine algorithm, where and when to use the SVM algorithm, and how Support Vector Machine works. You will learn about hyperplanes and support vectors, how distance margin helps in optimizing the hyperplane, kernel functions in SVM for data transformation and advantages of the SVM algorithm.

Below topics are explained in this Support Vector Machine Tutorial:
00:00 - 01:03 Applications and Agenda
01:04 - 01:58 What is Machine Learning?
01:58 - 03:39 Why support vector machine?
03:39 - 07:59 What is a support vector machine?
07:59 - 09:15 Advantages of support vector machine
09:15 - 26:42 Use Case in Python


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What is a Support Vector Machine?
Support Vector Machines are powerful supervised learning algorithms for both classification and regression. It is a discriminative classifier that is formally defined by a separating hyperplane. So given labelled training data, the algorithm outputs an optimal hyperplane that categorizes new examples.

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