https://www.support-vector.net/

I would suggest to read the following books, which provides information from basic to high on ML real world applications.

** If you want to learn ML using R-->

then go for "Machine Learning with R Cookbook " by Yu-Wei Chiu

which gives an idea about application of different models using R

Supervised learning --> using svm, k-nearest neighbor, bagging, boosting, random forest and many more

Unsupervised --> clustering, PCA etc.

** If you use python then I would suggest to go for

"Hands-On Machine Learning with Scikit-Learn & TensorFlow" by Aurélien Géron

One of the well written book for ML with basic theories and practical applications. It covers a separate chapter for Support Vector Machine.

You can find good tutorials about SVMs in Trevor Hastie's books here:

https://web.stanford.edu/~hastie/CASI_files/PDF/casi.pdf

http://www-bcf.usc.edu/~gareth/ISL/ISLR%20Sixth%20Printing.pdf

https://web.stanford.edu/~hastie/ElemStatLearn/printings/ESLII_print12.pdf

regards,

Bogdan

I need soft copy of this book " Machine Learning with R Cookbook " by Yu-Wei Chiu"

Thanks