Popular GitHub Repositories for Svms

recognize and localize an object in 3D Point Cloud scene using VFH - SVMs based method and 3D-CNNs method

Support vector machines (SVMs) and related kernel-based learning algorithms are a well-known class of machine learning algorithms, for non-parametric classification and regression. liquidSVM is an implementation of SVMs whose key features are: fully integrated hyper-parameter selection, extreme speed on both small and large data sets, full flexibility for experts, and inclusion of a variety of different learning scenarios: multi-class classification, ROC, and Neyman-Pearson learning, and least-squares, quantile, and expectile regression.

A C++ toolkit for Convex Optimization (Logistic Loss, SVM, SVR, Least Squares etc.), Convex Optimization algorithms (LBFGS, TRON, SGD, AdsGrad, CG, Nesterov etc.) and Classifiers/Regressors (Logistic Regression, SVMs, Least Squares Regression etc.)

Digit recognition using SVM

Self-Learning, Active and Passive Learning with SVMs and KMeans

Activities include Python basics, linear and logistic regression, cross-validation, tree-based methods, SVMs, deep learning, survival analysis, unsupervised learning, and multiple testing.