Support Vector Machine - SVM - Machine Learning Tutorial

Machine Learning is the king of today’s technologies. It supports various algorithms and Support Vector Machine (SVM) is its foundational algorithm. It is a supervised learning algorithm. The best part about Support Vector Machine is that it can be used as both a Classifier and a Regressor.

Support Vector Machine is highly preferred by many as it produces significant accuracy with very less computational power. The Support Vector Machine initially constructs a hyperplane or a set of hyperplanes which are used to divide or separate the different classes. It is called the Support Vector Machine because two nearest data points of the different classes support its formation.

Support Vector Machines have various applications such as they can be used in classification of images, in handwritten character recognition, classification of satellite SAR data. It is really an interesting topic and you can’t miss out on it. So, Stay tuned and watch the video till the end.

- Introduction.
Introduction to SVM.
How SVM looks in 2D Space.
Kernel SVM.
Some Parameters of SVM.
Industry Applications of SVM.
Demo.