awesome-mlops / awesome-ml-experiment-managementLinks
A curated list of awesome open source tools and commercial products for ML Experiment Tracking and Management π
β156Updated last year
Alternatives and similar repositories for awesome-ml-experiment-management
Users that are interested in awesome-ml-experiment-management are comparing it to the libraries listed below
Sorting:
- aim-mlflow integrationβ237Updated 2 years ago
- π Log and track ML metrics, parameters, models with Git and/or DVCβ185Updated this week
- AI Data Management & Evaluation Platformβ215Updated 2 years ago
- W&B Server is the self hosted version of Weights & Biasesβ342Updated last week
- Create powerful Hydra applications without the yaml files and boilerplate code.β448Updated last week
- π² A curated list of MLOps projects, tools and resourcesβ186Updated last year
- Codabench is a flexible, easy-to-use and reproducible benchmarking platform. Check our paper at Patterns Cell Press https://hubs.li/Q01fwβ¦β130Updated this week
- TorchFix - a linter for PyTorch-using code with autofix supportβ152Updated 5 months ago
- `mllint` is a command-line utility to evaluate the technical quality of Python Machine Learning (ML) projects by means of static analysisβ¦β80Updated 3 years ago
- spock is a framework that helps manage complex parameter configurations during research and development of Python applicationsβ142Updated 2 years ago
- Speed up model training by fixing data loading.β574Updated this week
- Recipes are a standard, well supported set of blueprints for machine learning engineers to rapidly train models using the latest researchβ¦β339Updated this week
- Distributed skorch on Ray Trainβ58Updated 3 years ago
- π¬ modelstore is a Python library that allows you to version, export, and save a machine learning model to your filesystem or a cloud stoβ¦β400Updated last year
- ClearML - Model-Serving Orchestration and Repository Solutionβ161Updated 3 weeks ago
- Experiment tracking server focused on speed and scalabilityβ117Updated last year
- Unified storage framework for the entire machine learning lifecycleβ155Updated last year
- Organize your experiments into discrete steps that can be cached and reused throughout the lifetime of your research project.β565Updated last year
- Common Python utilities and GitHub Actions in Lightning Ecosystemβ63Updated this week
- Modalities, a PyTorch-native framework for distributed and reproducible foundation model training.β93Updated this week
- Coarse-grained lineage and tracing for machine learning pipelines.β471Updated 3 years ago
- π·οΈ Git Tag Ops. Turn your Git repository into Artifact Registry or Model Registry.β158Updated last month
- Pytorch Lightning Distributed Accelerators using Rayβ215Updated 2 years ago
- A scalable & efficient active learning/data selection system for everyone.β217Updated last year
- Quadra: Effortless and reproducible deep learning workflows with configuration files.β50Updated last week
- Curated list of open source tooling for data-centric AI on unstructured data.β734Updated 2 years ago
- Introduction to Data-Centric AI, MIT IAP 2024 π€β105Updated 7 months ago
- ClearML Fractional GPU - Run multiple containers on the same GPU with driver level memory limitation β¨ and compute time-slicingβ88Updated 2 months ago
- MLOps Python Libraryβ121Updated 3 years ago
- API Client for paperswithcode.comβ189Updated last year