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DTSTART:20260308T030000
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DTSTART;TZID=America/Toronto:20201221T171500
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DTSTAMP:20210616T193733Z
CREATED:20210616
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SUMMARY:DSSS@UofT: Michael Hoffman
DESCRIPTION:Join us for the next installment of the Data Science Speaker Series at U of T with:\nMichael M. Hoffman\nSenior Scientist, Princess Margaret Cancer Centre\nAssociate Professor, Departments of Medical Biophysics and of Computer Science, University of Toronto\nFree Event | Registration Required\nTalk Title:\nEvaluating Machine Learning Claims\nAbstract:\nMachine learning has already changed many areas of our society, and there is the promise of it revolutionizing others. Why then is there sometimes a difference in the promises made and the reality found in terms of machine learning implementation and efficacy? We will explore how to separate hype from reality in evolving machine learning claims, including discussing what the point of machine learning is, the golden rule of machine learning evaluation, parameters versus hyperparameters, interpolation and extrapolation, and the advantages and disadvantages of statistics for evaluation such as the receiver operating characteristic (ROC) curve and the precision-recall (PR) curve.\nSpeaker Profile:\nMichael Hoffman creates predictive computational models to understand interactions between genome, epigenome, and phenotype in human cancers. He implemented the genome annotation method Segway, which simplifies interpretation of large multivariate genomic datasets, and was a linchpin of the NIH ENCODE Project analysis. He is a principal investigator at the Princess Margaret Cancer Centre and Associate Professor in the Departments of Medical Biophysics and Computer Science, University of Toronto. He was named a CIHR New Investigator and has received several awards for his academic work, including the NIH K99/R00 Pathway to Independence Award, and the Ontario Early Researcher Award.\n
URL:https://datasciences.utoronto.ca/event/dsssuoft_michael-hoffman/
CATEGORIES:DSSS@ U of T - 2021-2022 Season,DSSS@U of T
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