Support Vector Machine - How Support Vector Machine Works | SVM In Machine Learning | Simplilearn

This Support Vector Machine (SVM) tutorial video will help you understand the Support Vector Machine algorithm, where and when to use the SVM algorithm, how does the algorithm work, what are hyperplanes and support vectors in SVM, how distance margin helps in optimizing the hyperplane, kernel functions in SVM for data transformation and advantages of SVM algorithm. This video is a part of the Machine Learning with Python Series.

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Below topics are explained in this Support Vector Machine Tutorial:
0:00 Start
1. What is Machine Learning? ( 01:04 )
2. Why support vector machine? ( 01:58 )
3. What is a support vector machine? ( 03:39 )
4. Understanding the support vector machine ( 06:39 )
5. Advantages of support vector machine ( 07:59 )
6. Use case in Python ( 09:15 )

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3. Acquire thorough knowledge of the mathematical and heuristic aspects of Machine Learning.
4. Understand the concepts and operation of support vector machines, kernel SVM, Naive Bayes, decision tree classifier, random forest classifier, logistic regression, K-nearest neighbors, K-means clustering and more.
5. Be able to model a wide variety of robust Machine Learning algorithms including deep learning, clustering, and recommendation systems

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