Alan Mosca discusses using ensembles in deep learning and tackles a benchmark problem in computer vision with Toupee, a library and toolkit for experimentation with deep learning and ensembles based on Keras—starting from a simple convolutional network before building different types of ensembles. Alan covers traditional methods such as bagging and adaboost and more sophisticated “white box” ensembles that have been developed especially for deep learning.
Alan Mosca is the cofounder and CTO of nPlan and a part-time doctoral researcher at Birkbeck, University of London, where his research focuses on deep learning ensembles and improvements to optimization algorithms in deep learning. Previously, Alan worked at Wadhwani Asset Management, Jane Street Capital, and several software companies as well as on several consulting projects in machine learning and deep learning.
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