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.

  Read More

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.

  Read More

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.

  Read More