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SUMMARY:The Benefits of Bayesian Machine Learning - Stanley Lazic\, Cantab
DTSTART:20181108T113000Z
DTEND:20181108T123000Z
UID:TALK114256@talks.cam.ac.uk
CONTACT:Catherine Pearson
DESCRIPTION:Bayesian predictive models (a.k.a model-based machine learning
  or\nprobabilistic programming) have several advantages over classic machi
 ne\nlearning methods\, including the ability to incorporate and propagate 
 all\nsources of uncertainty and to include external information. In additi
 on\,\npredictions and model outputs are easy to interpret and there are ma
 ny\nways to check the model and understand where it goes wrong. Surprising
 ly\,\ncross-validation to tune hyperparameters is not required because\nhy
 perparameters can be learned from the data. The benefits of Bayesian ML\nw
 ill be discussed with examples from preclinical research in the\npharmaceu
 tical industry.\n\n
LOCATION:Open Plan Area\, BP Institute\, Madingley Rise CB3 0EZ
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