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Hi, I'm Matthew πŸ‘‹

Data scientist focusing on machine learning and predictive analytics. Currently, I work as a research scientist at Michigan Tech Research Institute, improving and implementing statistical methods for clients through developing scientific software, writing research proposals, creating and maintaining models, and wrangling new data sets. Previously, I was a computational scientist at the University of Illinois where I used numerical methods to expand the theory of computational plasmonics and was fortunate to be advised by David Nicholls. I also have experience with supercomputers and parallel processing at Argonne National Laboratory and finite element analysis at the Cold Regions Research and Engineering Laboratory. Prior to starting graduate school, I worked in Agile software development at Workforce Software and focused on data mining, numerical optimization, and software automation.


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Tech Stack

Ubuntu Git GitHub Jupyter Notebook Python NumPy SciPy Julia Keras TensorFlow scikit-learn Pandas Plotly Postgres LaTeX Qiskit


matthewshawnkehoe matthewshawnkehoe

Matthew's github activity graph

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matthewshawnkehoe


Matthew Kehoe's Projects

awesome-llm icon awesome-llm

Awesome-LLM: a curated list of Large Language Model

bookclub icon bookclub

Notes and links from the book club meetings

chebfun icon chebfun

Chebfun: numerical computing with functions.

data-science icon data-science

A collection of Jupyter Notebooks highlighting data science and machine learning projects.

fashion-mnist icon fashion-mnist

A MNIST-like fashion product database. Benchmark :point_down:

fiftyone icon fiftyone

The open-source tool for building high-quality datasets and computer vision models

gptq icon gptq

Code for the ICLR 2023 paper "GPTQ: Accurate Post-training Quantization of Generative Pretrained Transformers".

hops-awe-grating-scattering icon hops-awe-grating-scattering

A High–Order Perturbation of Surfaces/Asymptotic Waveform Evaluation (HOPS/AWE) algorithm for Grating Scattering Problems.

hydravit icon hydravit

HydraViT is a PyTorch implementation of the HydraViT model, an adaptive multi-branch transformer for multi-label disease classification from chest X-ray images. The repository provides the necessary code to train and evaluate the HydraViT model on the NIH Chest X-ray dataset.

iris-classification icon iris-classification

The Iris Dataset contains four features (length and width of sepals and petals) of 50 samples of three species of Iris (Iris setosa, Iris virginica and Iris versicolor). These measures were used to create a linear discriminant model to classify the species.

irradiance-forecast icon irradiance-forecast

This repo contains the code to forecast EUV irradiance 'Stan' bands from solar images up to six days in advance.

java-programs icon java-programs

Various Java programs for data and numerical analysis including an arbitrary precision complex number library.

llm-applications icon llm-applications

A comprehensive guide to building RAG-based LLM applications for production.

llm-course icon llm-course

Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.

llm.c icon llm.c

LLM training in simple, raw C/CUDA

llmspracticalguide icon llmspracticalguide

A curated list of practical guide resources of LLMs (LLMs Tree, Examples, Papers)

llmsurvey icon llmsurvey

The official GitHub page for the survey paper "A Survey of Large Language Models".

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