Learn Machine Learning

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Welcome! This is a place for people to learn more about machine learning techniques, discuss applications and ask questions.

Example questions:

"Should I use a deep neural network for my audio classification task?"
"I'm working with a small dataset, what can I do to make my model generalize well?"
"Is there a library available that implements function X in language Y?"
"I want to learn more about the math behind machine learning technique A, where should I start?"

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Introduction to Kernel Methods for Machine Learning (seis.bristol.ac.uk)

submitted 1 year ago by [email protected] to c/[email protected]

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Kernel methods give a systematic and principled approach to training learning machines and the good generalization performance achieved can be readily justified using statistical learning theory or Bayesian arguments. We describe how to use kernel methods for classification, regression and novelty detection and in each case we find that training can be reduced to optimization of a convex cost function.

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