iterative / workshop-uncool-mlopsLinks
Accompanies the uncool MLOps workshop
☆26Updated 3 years ago
Alternatives and similar repositories for workshop-uncool-mlops
Users that are interested in workshop-uncool-mlops are comparing it to the libraries listed below
Sorting:
- PyCon Talks 2022 by Antoine Toubhans☆23Updated 3 years ago
- Dvc + Streamlit = ❤️☆40Updated 2 years ago
- A PaaS End-to-End ML Setup with Metaflow, Serverless and SageMaker.☆37Updated 4 years ago
- Get started DVC project☆62Updated last year
- A list of projects relying on Iterative.AI tools to achieve awesomeness☆67Updated last year
- GitHub Action for CML setup☆30Updated last year
- 🐍 Material for PyData Global 2021 Presentation: Effective Testing for Machine Learning Projects☆82Updated 3 years ago
- Convert monolithic Jupyter notebooks 📙 into maintainable Ploomber pipelines. 📊☆79Updated last year
- A tutorial on how to use kedro-mlflow plugin (https://github.com/Galileo-Galilei/kedro-mlflow) to synchronize training and inference and …☆40Updated 3 years ago
- Machine Learning Projects with Flytekit☆36Updated 2 years ago
- Strategies to deploy deep learning models☆27Updated 7 years ago
- Dataset registry DVC project☆83Updated last year
- Tries to shrink your Pandas column dtypes with no data loss so you have more spare RAM☆84Updated last year
- ForML - A development framework and MLOps platform for the lifecycle management of data science projects☆106Updated 2 years ago
- Model Validation Toolkit is a collection of tools to assist with validating machine learning models prior to deploying them to production…☆29Updated last year
- Kedro Plugin to support running workflows on Kubeflow Pipelines☆55Updated 3 months ago
- 🏷️ Git Tag Ops. Turn your Git repository into Artifact Registry or Model Registry.☆153Updated last week
- Projects developed by Domino's R&D team☆77Updated 3 years ago
- 🚀 Stream inferences of real-time ML models in production to any data lake (Experimental)☆81Updated 3 years ago
- Best practices for engineering ML pipelines.☆36Updated 3 years ago
- Demo on how to use Prefect with Docker☆27Updated 3 years ago
- Pipeline components that support partial_fit.☆46Updated last year
- A repository that showcases how you can use ZenML with Git☆71Updated 2 months ago
- Templates for your Kedro projects.☆79Updated last week
- dask-pytorch-ddp is a Python package that makes it easy to train PyTorch models on dask clusters using distributed data parallel.☆59Updated 4 years ago
- The easiest way to integrate Kedro and Great Expectations☆54Updated 2 years ago
- 📈 Log and track ML metrics, parameters, models with Git and/or DVC☆181Updated last week
- An efficient, to-the-point, and easy-to-use checklist to following when deploying an ML model into production.☆30Updated 2 years ago
- Scaling Python Machine Learning☆50Updated 2 years ago
- Chassis turns machine learning models into portable container images that can run just about anywhere.☆86Updated last year