endric-daues
Machine Learning Engineer @Tinder. Operations Research and Applied Mathematics at Columbia Engineering. Interested in optimization and deep learning.
Los Angeles, CA
Pinned Repositories
IoT_Programming
Slides from our IoT Programming Series using the Raspberry Pi.
apma4302
Class work for apma4302
ipcauchy
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.
my_setup
Configuration I use for developing.
parallel_ipcauchy
A parallel implementation of the IPCauchy Code for the final project in APMA E4302, taught by Kyle Mandli.
pymusic_theory
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.
stanford_datathon
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.
transformers
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.
endric-daues's Repositories
endric-daues/ipcauchy
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.
endric-daues/apma4302
Class work for apma4302
endric-daues/my_setup
Configuration I use for developing.
endric-daues/parallel_ipcauchy
A parallel implementation of the IPCauchy Code for the final project in APMA E4302, taught by Kyle Mandli.
endric-daues/pymusic_theory
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.
endric-daues/stanford_datathon
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.
endric-daues/transformers
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.