Name: Endric Daues
Type: User
Bio: Machine Learning Engineer @Tinder.
Operations Research and Applied Mathematics at Columbia Engineering.
Interested in optimization and deep learning.
Location: Los Angeles, CA
Blog: www.endricdaues.com
Endric Daues's Projects
Class work for apma4302
A python implementation of the algorithm described in (https://pubsonline.informs.org/doi/abs/10.1287/ijoc.2021.1142) to count feasible solutions to hard integer programs.
Configuration I use for developing.
A parallel implementation of the IPCauchy Code for the final project in APMA E4302, taught by Kyle Mandli.
A collection of Python classes and methods to help me build an intuition around some basic musical theory. I continue to use some of the visualizations here during practice.
Submission for the 2020 Blueprint Stanford Hackathon. We implemented a LSTM Neural Network to predict week over week changes in Covid case counts for various US counties given social mobility data.
Repository to train, understand, and experiment with transformer models. The ML code is largely based on Kaparthy's nanoGPT repo (https://github.com/karpathy/nanoGPT), however, the monolithic scripts have been broken down into a more user friendly class structure, and several notebooks deep dive into the code details.