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Lecture
Are you an EPFL student looking for a semester project?
Work with us on data science and visualisation projects, and deploy your project as an app on top of Graph Search.
This lecture covers Kernel Methods in Machine Learning, focusing on topics such as overfitting vs underfitting, model selection, validation set method, LOOCV, k-fold cross-validation, penalizing overfitting, regularized linear regression, polynomial feature expansion, kernel functions, Gaussian kernel, polynomial kernel, feature expansion properties, kernel trick, kernel regression, Representer theorem, multi-output linear regression, kernelization, SVM dual formulation, prediction, kernel SVM, and kernel methods advantages and drawbacks.