Stars
Demonstrate the use of ops tools to automate ML workflow
A curated list of awesome C++ (or C) frameworks, libraries, resources, and shiny things. Inspired by awesome-... stuff.
Collection of various algorithms in mathematics, machine learning, computer science and physics implemented in C++ for educational purposes.
The VECMA toolkit for creating surrogate models of multiscale systems.
Models for analyzing energy–performance trade-offs. This repository is intended to: a) launch GPU benchmarks, b) collect GPU metrics, including power consumption, and c) analyze GPU power consumpti…
Free MLOps course from DataTalks.Club
📚 A Collection of Free & Open Resources for University Coursework in Computer Science.
A cross-platform C and C++ unit testing framework for the 21st century
All Algorithms implemented in Python
Disease Informed Neural Networks (DINNs) — neural networks capable of learning how diseases spread, forecasting their progression, and finding their unique parameters (e.g. death rate).
Library for exploring and validating machine learning data
Chaospy - Toolbox for performing uncertainty quantification.
Uncertainpy: a Python toolbox for uncertainty quantification and sensitivity analysis, tailored towards computational neuroscience.
Sensitivity Analysis Library in Python. Contains Sobol, Morris, FAST, and other methods.
Python 3 framework to facilitate verification, validation and uncertainty quantification (VVUQ) for a wide variety of simulations.
MPI programming lessons in C and executable code examples
Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.