Stars
The property-based testing library for Python
The live data layer for apps and AI agents Create up-to-the-second views into your business, just using SQL
🌊 Julia software for fast, friendly, flexible, ocean-flavored fluid dynamics on CPUs and GPUs
Library for building distributed, real-time collaborative web applications
QuestDB is a high performance, open-source, time-series database
This is an online course where you can learn and master the skill of low-level performance analysis and tuning.
The financial transactions database designed for mission critical safety and performance.
JupyterBook source for The Climate Laboratory
Some notes on things I find interesting and important.
List of single-file C/C++ libraries, with emphasis on clause-less licenses.
stb single-file public domain libraries for C/C++
A hash table with consistent order and fast iteration; access items by key or sequence index
Algorithms from circuit theory to predict connectivity in heterogeneous landscapes
Curating a list of AutoML-related research, tools, projects and other resources
Mobilize Center Tutorials
A guideline for building practical production-level deep learning systems to be deployed in real world applications.
Bone deformation tool designed for applying torsional profiles to bones of musculoskeletal models used in OpenSim
A minimalist Jekyll theme for running a personal blog powered by Jekyll and GitHub Pages
OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation
Chalk is a high quality, completely customizable, performant and 100% free Jekyll blog theme.
re is a ✨CLI ✨code review tool for GitHub. Do code reviews from the comfort of your $EDITOR!
Comparing fairness-aware machine learning techniques.
Official repo for the Materialize + Redpanda + dbt Hack Day 2022, including a sample project to get everyone started!
This fork of BVLC/Caffe is dedicated to improving performance of this deep learning framework when running on CPU, in particular Intel® Xeon processors.
Code for reproducing results in Delayed Impact of Fair Machine Learning (Liu et al 2018)