Alan Jeffares

elements-of-statistical-learning. Documenting my progress as I work through The Elements of Statistical Learning book by T. Hastie, R. Tibshirani, and J. Friedman

discreteVAE. Code for our tutorial on Discrete Variational Autoencoders

notebook-to-microservice. Sample repository (to accompany my blog post) for putting machine learning code into production.

TANGOS. Implementation of Tabular Neural Gradient Orthogonalization and Specialization (TANGOS). A regularizer for neural networks described in our ICLR 2023 paper.

data-science-nanodegree. My complete solutions to the four projects undertaken as part of the Udacity Data Science nanodegree

joint-ensembles. Python

not-double-descent. Python

telescoping-lens.

subtractive-clustering. My implementation of the subtractive clustering algorithm as described in Sheng-Wu Xiong, Xiao-Xiao Niu and Hong-Bing Liu, (2005)

super-learner. My implementation of the stacked ensemble Super Learner as described in Mark J. van der Laan et al, (2007)

mclust-app. An R Shiny application implementing mclust, a popular R package for model based clustering and classification

lunar-lander. Comparing ML against RL for beating OpenAI's Lunar Lander game