Paul Rigor's repositories
workshop
AI and Machine Learning with Kubeflow, Amazon EKS, and SageMaker
aws-deployment-framework
The AWS Deployment Framework (ADF) is an extensive and flexible framework to manage and deploy resources across multiple AWS accounts and regions based on AWS Organizations.
backstage
Backstage is an open platform for building developer portals
cicd-pipeline-train-schedule-git
Train Schedule sample app for Git exercises
ColabFold
Making Protein folding accessible to all!
d2l-en
Dive into Deep Learning: an interactive deep learning book with code, math, and discussions
dbt-core
dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.
deep-learning-containers
AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet.
docker-ghidra
Ghidra Client/Server Docker Image
exachem
Open Source Exascale Computational Chemistry Software
GauXC
GauXC is a modern, modular C++ library for the evaluation of quantities related to the exchange-correlation (XC) energy (e.g. potential, etc) in the Gaussian basis set discretization of Kohn-Sham density function theory (KS-DFT) on heterogenous architectures.
hpc-toolset-tutorial
Tutorial for installing Open XDMoD, OnDemand, & ColdFront
jupyter_plz
Copilot for Jupyter notebooks.
langchain
🦜🔗 Build context-aware reasoning applications
mlops-e2e
MLOps End-to-End Example using Amazon SageMaker Pipeline, AWS CodePipeline and AWS CDK
multi-region-python-package-publishing-pipeline
This git repository is designed to demonstrate how to build and publish pip packages to CodeArtifact Repositories in Multiple Regions by using CodePipeline and the AWS CDK.
NeMo
NeMo: a framework for generative AI
Open-Catalyst-Dataset
Workflow for creating and analyzing the Open Catalyst Dataset
openfold
Trainable, memory-efficient, and GPU-friendly PyTorch reproduction of AlphaFold 2
optimum-neuron
Easy, fast and very cheap training and inference on AWS Trainium and Inferentia chips.
pandas
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
pytorch-lightning
Pretrain, finetune and deploy AI models on multiple GPUs, TPUs with zero code changes.
ray
Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
shrink-linalg
Sample python on how to shrink the footprint of NumPy, SciPy, Pandas, and Matplotlib Python libraries
terraform-aws-gitlab-runner-scale
Gitlab runners created via Lambda check