ML algorithm and projects

SVM Support Vector Machines is a supervised machine learning approach which will help in solving both classification and regression problems.  In the below figure, we have two class of data (red squares and blue circles). The center line is called as hyperplane and helps in classifying the two classes. The hyperplane will create two margin lines with a distance. These margin lines are the parallel line which will pass through the nearest point(s)( support vectors ) of each class(line can pass through any number of points if the nearest points are equidistant from the hyperbola). There can be any kind of hyperplane(vertical/horizontal) but what depends on the hyperplane selection is the marginal distance that is formed. Here the dotted lines as mentioned are called margin lines and the distance between them is called marginal distance (more the distance better the model is). So in this case, we can say that classes are easily separable using the hyperbola that is they are linearly sepa