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+DS vLE: Introduction to Gaussian processes for Machine Learning

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Thursday, November 18, 2021
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11:00 am - 12:00 pm
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Mauricio A Álvarez

In this session, Prof. Mauricio Álvarez will define a Gaussian process (GP) model and describe how it is used to tackle (non-linear) regression problems including defining the kernel function, the key function that defines the Gaussian process. He will define how we can use optimization of the marginal likelihood to estimate (hyper-)parameters in the GP model, and (time permitting) how GPs are used for pattern classification, multiple-output regression, unsupervised learning and Bayesian optimization.

Mauricio A Álvarez, PhD. is an Associate Professor in the Department of Computer Science at The University of Sheffield in the United Kingdom.

This session is part of the Duke+DataScience (+DS) program virtual learning experiences (vLEs). To learn more, please visit https://plus.datascience.duke.edu