Bank Marketing Strategy

Posted by Christopher Mertin on August 21, 2017 in Project • 13 min read

Using statistics, deep learning, SVMs, and Gaussian Mixture Models on customer banking information to build a predictive model to optimize who the bank markets term deposits to so that marketing resources are not wasted on those unlikely to enroll.


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Searching for Exotic Particles in High Energy Physics

Posted by Christopher Mertin on June 09, 2017 in Project • 8 min read

Using data pertaining to Super Symmetry (susy), I explore the use of various algorithms to try and identify particles from data. I look at the use of a Random Forest, Gaussian Na├»ve Bayes, Multi-Layer Perceptron, and Deep Learning with the use of Dropout.


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Efficient Deep Neural Networks

Posted by Christopher Mertin on May 05, 2017 in Project • 2 min read

Masters project at the Univeristy of Utah which explores the use of Hierarchical Matrices to increase the learning rate and computation speed of Deep Neural Networks.


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