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University of Cambridge > Talks.cam > Cambridge Centre for Analysis talks > Machine Learning in Academia vs. Industry: Tech-to-problem fit on 3 example projects
Machine Learning in Academia vs. Industry: Tech-to-problem fit on 3 example projectsAdd to your list(s) Download to your calendar using vCal
If you have a question about this talk, please contact CCA. Industrial seminar It is one thing to optimise Machine Learning (ML) work for publication; and a very different one to put it in production, providing value in the economy. In his talk, Meelis will discuss different perspectives of doing useful things with ML, and putting deep technology ideas into practice, based on 3 of his past projects. Bio: Meelis completed his Computer Vision & ML PhD at VGG at Oxford University in 2015, where he developed ML models to diagnose back pain MRI scans. This led to licensing of the models to industry, and the subsequent quest for best practically valuable applications of machine learning models. After his PhD, Meelis worked in finance and on three different startup ideas in Entrepreneur First. This talk is part of the Cambridge Centre for Analysis talks series. This talk is included in these lists:
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