Embedded And Real Time Systems Optimization Exam Study Material for Gate ECE

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Support Vector Machines Introduction, obtaining the optimal hyperplane	lec31	30:45 to 31:19	PDF	VIDEO
Support Vector Machines Introduction, obtaining the optimal hyperplane	lec31	56:58 to upto	PDF	VIDEO
Support Vector Machines Introduction, obtaining the optimal hyperplane	lec32	30:45 to 31:19	PDF	VIDEO
Support Vector Machines Introduction, obtaining the optimal hyperplane	lec32	56:58 to upto	PDF	VIDEO
SVM formulation with slack variables; non-linear SVM classifiers	lec33	17:55 to 19:19	PDF	VIDEO
Kernel Functions for non-linear SVMs; Mercer and positive definite Kernels	lec34	01:29 to 03:50	PDF	VIDEO
Kernel Functions for non-linear SVMs; Mercer and positive definite Kernels	lec34	03:50 to 05:37	PDF	VIDEO
Overview of SMO and other algorithms for SVM; v-SVM and v-SVR; SVM as a risk minimizer	lec36	03:10 to 05:11	PDF	VIDEO