
An Introduction to Support Vector Machines and Other Kernel-Based Learning Methods
Sign in to keep track of books you’ve read and want to read.
This is the first comprehensive introduction to Support Vector Machines (SVMs), a new generation learning system based on recent advances in statistical learning theory. Students will find the book both stimulating and accessible, while practitioners will be guided smoothly through the material required for a good grasp of the theory and its applications. The concepts are introduced gradually in accessible and self-contained stages, while the presentation is rigorous and thorough. Pointers to relevant literature and web sites containing software make it an ideal starting point for further study.
Liked An Introduction to Support Vector Machines and Other Kernel-Based Learning Methods? Here’s where I’d start.
These suit anyone who liked An Introduction to Support Vector Machines and Other Kernel-Based Learning Methods. Sign in and mark a few books for picks shaped around your own taste.
-
Pattern Classification Shares machine learning, data science, computer science -
Pattern Recognition and Machine Learning Shares machine learning, data science, computer science -
Machine Learning Shares machine learning, computer science, data science -
The Elements of Statistical Learning: Data Mining, Inference, and Prediction Shares machine learning, data science, technical