GitHub Projects & Software
Below is a selection of my open-source projects, statistical packages, and machine learning implementations. You can find all of my source code and contributions on my GitHub profile.
Statistical Packages
A Bayesian sum-of-trees model designed to incoporate measurement error in predictor
variables, with applications in medical and clinical research.
A Bayesian sum-of-trees model designed to handle semi-supervised learning problems with
multiple
instance learning (MIL) data structures, where observations are organized into bags and
only
bag-level labels are observed.
Standalone Projects
An Exploration of Bayesian Quantile Regression and Comparison to Other Methods
Extension of John Tukey's 'Mathematics and the Picturing of Data' into Three Dimensions
Recreations of Popular Algorithms
A simple implementation of the CART algorithm in Python, designed for educational
purposes to
illustrate the fundamentals of decision tree learning.
A simple implementation of feedforward neural networks in Python, designed for
educational purposes to illustrate the fundamentals of deep learning and
backpropagation.
A simple implementation of the EM algorithm for fitting Gaussian mixture models in R,
designed for
educational purposes to illustrate the fundamentals of probabilistic modeling.