High-Performance Symbolic Regression in Python and Julia
The open standard for data logging
Benchmarking synthetic data generation methods
Easy integration with Athena, Glue, Redshift, Timestream, Neptune
Scientific Visualisation Made Easy
Clean Jupyter notebooks of outputs, metadata, and empty cells
A toolkit to run Ray applications on Kubernetes
Detecting silent model failure. NannyML estimates performance
Package to make C++ libraries available in Julia
Pandas on AWS, easy integration with Athena, Glue, Redshift, etc.
Train machine learning models within Docker containers
Stream Processing and Complex Event Processing Engine
Scalable and Flexible Gradient Boosting
import code from IJulia Jupyter notebooks into Julia programs
Simple and distributed Machine Learning
A library for scientific data visualization
Cross-platform, scientific graphics plotting library
Real-time, incremental ETL library for ML with record-level depend
a package with useful scripts for X-ray diffraction physicists
Statistical data visualization in Python
OpenPTV
MCPower — simple Monte Carlo power analysis for complex models
CEED Library: Code for Efficient Extensible Discretizations