matthewshawnkehoe
Data and research scientist with a background in computational mathematics. Passionate about machine learning and scientific software development.
Ann Arbor, MI
Pinned Repositories
Gross-Pitaevskii-Eigenvalue-problem
A project on Gross–Pitaevskii eigenvalue problem using Machine learning method
Ann-Arbor-AI-ML-Group
Material and projects from the Ann Arbor AI/ML Meetup group
Data-Science
A collection of Jupyter Notebooks highlighting data science and machine learning projects.
Data-Science-Machine-Learning-Collaborative-Learning-Group
Material and projects from the Data Science & Machine Learning Collaborative Learning Meetup group
deep-learning-with-python-notebooks
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
HOPS-AWE-Grating-Scattering
A High–Order Perturbation of Surfaces/Asymptotic Waveform Evaluation (HOPS/AWE) algorithm for Grating Scattering Problems.
matthewshawnkehoe.github.io
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
Riemann-Zeta-Functions
Computer implementation of the Riemann Siegel formula in Julia alongside various plotting and numerical programs related to the Riemann zeta function.
matthewshawnkehoe's Repositories
matthewshawnkehoe/Data-Science-Machine-Learning-Collaborative-Learning-Group
Material and projects from the Data Science & Machine Learning Collaborative Learning Meetup group
matthewshawnkehoe/HOPS-AWE-Grating-Scattering
A High–Order Perturbation of Surfaces/Asymptotic Waveform Evaluation (HOPS/AWE) algorithm for Grating Scattering Problems.
matthewshawnkehoe/Ann-Arbor-AI-ML-Group
Material and projects from the Ann Arbor AI/ML Meetup group
matthewshawnkehoe/matthewshawnkehoe.github.io
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
matthewshawnkehoe/3D_SAR
3D SAR construction algorithm
matthewshawnkehoe/accelerate
🚀 A simple way to launch, train, and use PyTorch models on almost any device and distributed configuration, automatic mixed precision (including fp8), and easy-to-configure FSDP and DeepSpeed support
matthewshawnkehoe/ApproxFun.jl
Julia package for function approximation
matthewshawnkehoe/chebfun
Chebfun: numerical computing with functions.
matthewshawnkehoe/datasets
🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools
matthewshawnkehoe/deepxde
A library for scientific machine learning and physics-informed learning
matthewshawnkehoe/fiftyone
The open-source tool for building high-quality datasets and computer vision models
matthewshawnkehoe/flair
A very simple framework for state-of-the-art Natural Language Processing (NLP)
matthewshawnkehoe/GPT-PINN
Generative Pre-Trained Physics-Informed Neural Networks Implementation
matthewshawnkehoe/Gross-Pitaevskii-Eigenvalue-problem
A project on Gross–Pitaevskii eigenvalue problem using Machine learning method
matthewshawnkehoe/ipie
ipie stands for Intelligent Python-based Imaginary-time Evolution with a focus on simplicity and speed.
matthewshawnkehoe/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.
matthewshawnkehoe/JuliaDataScience
Book on Julia for Data Science
matthewshawnkehoe/langchain
🦜🔗 Build context-aware reasoning applications
matthewshawnkehoe/large-language-models
Notebooks for Large Language Models (LLMs) Specialization
matthewshawnkehoe/LLMs-from-scratch
Implementing a ChatGPT-like LLM from scratch, step by step
matthewshawnkehoe/Machine-Learning-Projects
Data Science Projects for Natural Language Processing and Supervised/ Unsupervised Machine Learning
matthewshawnkehoe/Makie.jl
Interactive data visualizations and plotting in Julia
matthewshawnkehoe/Neural-PDE-Solver
List of papers using variations of PINNs to solve PDEs
matthewshawnkehoe/notebooks
Notebooks using the Hugging Face libraries 🤗
matthewshawnkehoe/pytorch-image-models
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more
matthewshawnkehoe/scikit-llm
Seamlessly integrate LLMs into scikit-learn.
matthewshawnkehoe/Textbook-Solutions
A collection of textbook solutions written in LaTeX.
matthewshawnkehoe/tokenizers
💥 Fast State-of-the-Art Tokenizers optimized for Research and Production
matthewshawnkehoe/transformers
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
matthewshawnkehoe/yolov10
YOLOv10: Real-Time End-to-End Object Detection