Join us for the Data Science Speaker Series at U of T with Michael Hoffman

Professor Michael 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 currently a principal investigator at 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.

Talk Title:

Evaluating Machine Learning Claims

Abstract:

Machine 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.

Seminars are held every third Monday of each month, from October to May, 5:15-6:15 pm EST.

The Data Science Speaker Series at U of T (DSSS) is the result of a collaboration of Data Science programs at the University of Toronto.

Together, we seek to advance knowledge in the field of data science by featuring world-class speakers from academic, healthcare, industry, finance, technology, sports, and other sectors and industries.

In doing so, we hope to facilitate the exchange of ideas, information, and knowledge among scientists, practitioners, and other professionals, and to enhance educational opportunities for students and trainees.

See here for more details and a complete schedule for DSSS.