In this video, we'll give an Introduction to Support Vector Machines. we'll implement Support Vector Machines using SciKit-Learn Library!
SVM are supervised learning models with associated learning algorithms that analyse data used for classification and regression analysis. Given a set of training examples, each marked as belonging to one or the other of two categories, an SVM training algorithm builds a model that assigns new examples to one category or the other, making it a non-probabilistic binary linear classifier. Blog and Videos for in-depth understanding : 1. https://www.youtube.com/watch?v=efR1C6CvhmE
2. http://andybromberg.com/svm-intuition/
3. https://medium.com/machine-learning-101/chapter-2-svm-support-vector-machine-theory-f0812effc72
4. https://stackabuse.com/implementing-svm-and-kernel-svm-with-pythons-scikit-learn/ About Rounak Vyas:
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