iterative / awesome-iterative-projectsLinks
A list of projects relying on Iterative.AI tools to achieve awesomeness
β68Updated last year
Alternatives and similar repositories for awesome-iterative-projects
Users that are interested in awesome-iterative-projects are comparing it to the libraries listed below
Sorting:
- π² A curated list of MLOps projects, tools and resourcesβ186Updated last year
- π·οΈ Git Tag Ops. Turn your Git repository into Artifact Registry or Model Registry.β158Updated last month
- Learn how to create reliable ML systems by testing code, data and models.β91Updated 3 years ago
- Get started DVC project (NLP, random forest)β190Updated last year
- A repository that showcases how you can use ZenML with Gitβ74Updated 3 weeks ago
- The Fuzzy Labs guide to the universe of open source MLOpsβ476Updated 8 months ago
- A simple guide to MLOps through ZenML and its various integrations.β188Updated 2 years ago
- Example project with a complete MLOps cycle: versioning data, generating reports on pull requests and deploying the model on releases witβ¦β49Updated 4 years ago
- A series of Terraform based recipes to provision popular MLOps stacks on the cloud.β256Updated last year
- Dvc + Streamlit = β€οΈβ40Updated 2 years ago
- π Log and track ML metrics, parameters, models with Git and/or DVCβ185Updated 2 weeks ago
- Machine learning experiment tracking and data versioning with DVC extension for VS Codeβ216Updated this week
- βοΈ Terraform plugin for machine learning workloads: spot instance recovery & auto-termination | AWS, GCP, Azure, Kubernetesβ294Updated last year
- Demo DVC project training a classification model on tabular dataβ41Updated last year
- Dataset registry DVC projectβ85Updated last year
- An open-source AutoML Library based on PyTorchβ309Updated last month
- DagsHub client librariesβ101Updated last week
- π Python project template with unit tests, code coverage, linting, type checking, Makefile wrapper, and GitHub Actions.β152Updated last year
- skops is a Python library helping you share your scikit-learn based models and put them in productionβ512Updated last week
- A curated list of awesome open source tools and commercial products for monitoring data quality, monitoring model performance, and profilβ¦β92Updated last year
- Learn how to monitor ML systems to identify and mitigate sources of drift before model performance decay.β96Updated 3 years ago
- π Stream inferences of real-time ML models in production to any data lake (Experimental)β81Updated 3 years ago
- β30Updated 3 years ago
- Practical Deep Learning at Scale with MLFlow, published by Packtβ163Updated last month
- It's all in the nameβ82Updated 2 years ago
- Joining the modern data stack with the modern ML stackβ201Updated 2 years ago
- Streamline scikit-learn model comparison.β142Updated 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
- π Minimal examples of machine learning tests for implementation, behaviour, and performance.β265Updated 3 years ago
- β Eurybia monitors model drift over time and securizes model deployment with data validationβ215Updated 2 months ago