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https://towardsdatascience.com/support-vector-machine-introduction-to-machine-learning-algorithms-934a444fca47
Jun 07, 2018 · Introduction. I guess by now you would’ve accustomed yourself with linear regression and logistic regression algorithms. If not, I suggest you have a look at them before moving on to support vector machine. Support vector machine is another simple algorithm that every machine learning expert should have in his/her arsenal.Author: Rohith Gandhi
https://www.youtube.com/watch?v=gidJbK1gXmA
Aug 12, 2016 · Introduction Support Vector Machine ... Support Vector Machine ... 5 Minutes Engineering 70,461 views. 7:47. 11. Introduction to Machine Learning - Duration: ...Author: Machine Learning- Sudeshna Sarkar
https://dataaspirant.com/2017/01/13/support-vector-machine-algorithm/
Jan 13, 2017 · Support Vector Machine Libraries / Packages: For implementing support vector machine on a dataset, we can use libraries. There are many libraries or packages available that can help us to implement SVM smoothly. We just need to call functions with parameters according to our need. In Python, we can use libraries like sklearn.
https://docs.opencv.org/2.4/doc/tutorials/ml/introduction_to_svm/introduction_to_svm.html
A Support Vector Machine (SVM) is a discriminative classifier formally defined by a separating hyperplane. In other words, given labeled training data (supervised learning), the algorithm outputs an optimal hyperplane which categorizes new examples. In which sense is the hyperplane obtained optimal? Let’s consider the following simple problem:
https://towardsdatascience.com/introduction-to-support-vector-machine-svm-4671e2cf3755
Jan 21, 2019 · Support vector machine (SVM) The support vector machine is an extension of the support vector classifier that results from enlarging the feature space using kernels. The kernel approach is simply an efficient computational approach for accommodating a non-linear boundary between classes.Author: Marco Peixeiro
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