🦉 Data Versioning and ML Experiments
☁️ 🚀 📊 📈 Evaluating state of the art in AI
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. ⚡🔥⚡
This is the development home of the workflow management system Snakemake. For general information, see
Accelerated deep learning R&D
Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.
A toolkit for reproducible reinforcement learning research.
🦖 ClawBio - The first bioinformatics-native AI agent skill library. Local-first. Reproducible. Open. Free.
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.
RNA-seq workflow using STAR and DESeq2
Get started DVC project (NLP, random forest)
Unifying Variational Autoencoder (VAE) implementations in Pytorch (NeurIPS 2022)
The open‑source AI Agents Governance & Orchestration framework: write the rules declaratively, Bernstein enforces them and produces the verifiable, replayable record. Free, Apache-2.0. https://bernstein.run
Open solution to the Home Credit Default Risk challenge 🏡
This Snakemake pipeline implements the GATK best-practices workflow
Create highly reproducible python environments
Relational Workflows: where database schemas define executable data pipelines.
Tool for encapsulating, running, and reproducing data science projects
High-fidelity performance metrics for generative models in PyTorch
To associate your repository with the reproducibility topic, visit your repo's landing page and select "manage topics."