Soft Computing Models Of Neural Networks Exam Study Material for Gate ECE

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Overview of Artificial Neural Networks	lec26	15:30 to 16:52	PDF	VIDEO
Overview of Artificial Neural Networks	lec26	16:52 to 19:34	PDF	VIDEO
Multilayer Feedforward Neural networks with Sigmoidal activation functions	lec27	00:43 to 02:15	PDF	VIDEO
Backpropagation Algorithm; Representational Abilities of Feedforward Networks	lec28	29:30 to 31:45	PDF	VIDEO
Feedforward networks for Classification and Regression; Back propagation in Practice	lec29	29:16 to 31:02	PDF	VIDEO
Feedforward networks for Classification and Regression; Back propagation in Practice	lec29	55:52 to 56:20	PDF	VIDEO
Radial Basis Function Networks; Gaussian RBF networks	lec30	00:38 to 03:15	PDF	VIDEO
No Free Lunch Theorem; Model selection and model estimation; Bias-variance trade-off	lec39	32:04 to 34:04	PDF	VIDEO
No Free Lunch Theorem; Model selection and model estimation; Bias-variance trade-off	lec39	34:04 to 35:15	PDF	VIDEO