🦉 Data Versioning and ML Experiments
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Updated
Dec 2, 2024 - Python
🦉 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 toolkit for reproducible reinforcement learning research.
Unifying Variational Autoencoder (VAE) implementations in Pytorch (NeurIPS 2022)
☁️ 🚀 📊 📈 Evaluating state of the art in AI
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
Dev environments for numerous languages based on Nix flakes [maintainer=@lucperkins]
Presentation-Ready Data Summary and Analytic Result Tables
Simplified nix packaging for various programming language ecosystems [maintainer=@DavHau]
High-fidelity performance metrics for generative models in PyTorch
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.
Function-oriented Make-like declarative workflows for R
Create highly reproducible python environments
Workflow Description Language - Specification and Implementations
Add a description, image, and links to the reproducibility topic page so that developers can more easily learn about it.
To associate your repository with the reproducibility topic, visit your repo's landing page and select "manage topics."