🦉 Data Versioning and ML Experiments

The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.

PyTorch Lightning + Hydra. A very user-friendly template for ML experimentation. ⚡🔥⚡

Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.

Accelerated deep learning R&D

This is the development home of the workflow management system Snakemake. For general information, see

A library of enterprise-grade AI agents designed to democratize artificial intelligence and provide free, open-source alternatives to overvalued Y Combinator startups. If you are excited about democratizing AI access & AI agents, please star ⭐️ this repository and use the link in the readme to join our open source AI research team.

Dev environments for numerous languages based on Nix flakes [maintainer=@lucperkins]

A toolkit for reproducible reinforcement learning research.

:cloud: :rocket: :bar_chart: :chart_with_upwards_trend: Evaluating state of the art in AI

Unifying Variational Autoencoder (VAE) implementations in Pytorch (NeurIPS 2022)

The collaboration workspace for Machine Learning

A comparison between some VPS providers. It uses Ansible to perform a series of automated benchmark tests over the VPS servers that you specify. It allows the reproducibility of those tests by anyone that wanted to compare these results to their own. All the tests results are available in order to provide independence and transparency.

An R-focused pipeline toolkit for reproducibility and high-performance computing

Simplified nix packaging for various programming language ecosystems [maintainer=@DavHau]

Presentation-Ready Data Summary and Analytic Result Tables

High-fidelity performance metrics for generative models in PyTorch

Function-oriented Make-like declarative workflows for R

This is the repository of our article published in RecSys 2019 "Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches" and of several follow-up studies.

Create highly reproducible python environments

Specification for the Workflow Description Language (WDL).

Prepare Raspberry Pi 3, 4 & 5 configurations using a virtual machine.

Render bits of R code for sharing, e.g., on GitHub or StackOverflow.

Declarative and reproducible Jupyter environments - powered by Nix

rrtools: Tools for Writing Reproducible Research in R

Generic template to bootstrap your PyTorch project.

Quantus is an eXplainable AI toolkit for responsible evaluation of neural network explanations

[CVPR 2020 Workshop] A PyTorch GAN library that reproduces research results for popular GANs.

LabNotebook is a tool that allows you to flexibly monitor, record, save, and query all your machine learning experiments.

Open solution to the Home Credit Default Risk challenge :house_with_garden: