SVM recommended reading literature and blog, SVM reading literature blog
SVM is a classic classification algorithm. There are many wonderful blog posts and books on the Internet. Today I will summarize these materials and thank you for sharing them!
[1] The author of JerryLead's blog gave a smooth and popular derivation based on Stanford's handouts: SVM series.
[2] Jia shiber's SVM getting-started series is very good.
[3] pluskid Support Vector Machine Series, very good. The derivation of dual is awesome.
[4] Leo Zhang's SVM Learning Series. His blog also contains many other machine learning algorithms.
[5] v_july_v introduction to SVM (understanding the three-layer realm of SVM ). Structure-based algorithm blog.
[6] Li Hang's statistical learning method, Tsinghua University Press
[7] SVM Learning -- Sequential Minimal Optimization
[8] SVM algorithm implementation (1)
[9] Sequential Minimal Optimization: A FastAlgorithm for Training Support Vector Machines
[10] SVM-from "Principle" to implementation
[11] SVM getting started Series
[12] SVM versions and their multi-language implementation code collection
[13] Karush-Kuhn-Tucker (KKT) conditions
[14] a deep understanding of the conditions of the Laplace Multiplier and KKT
[15] Machine Learning Algorithms and python practices