awesome-mlops / awesome-ml-monitoring
A curated list of awesome open source tools and commercial products for monitoring data quality, monitoring model performance, and profiling data 🚀
☆64Updated 6 months ago
Related projects ⓘ
Alternatives and complementary repositories for awesome-ml-monitoring
- A repository that showcases how you can use ZenML with Git☆66Updated 3 months ago
- Frouros: an open-source Python library for drift detection in machine learning systems.☆194Updated this week
- Example project with a complete MLOps cycle: versioning data, generating reports on pull requests and deploying the model on releases wit…☆45Updated 3 years ago
- MLOps maturity assessment☆57Updated last year
- 🐍 Material for PyData Global 2021 Presentation: Effective Testing for Machine Learning Projects☆81Updated 2 years ago
- Template repo for kickstarting recipes for regression use case☆50Updated 6 months ago
- A series of Terraform based recipes to provision popular MLOps stacks on the cloud.☆249Updated last month
- Streamline scikit-learn model comparison.☆146Updated last year
- 🛠 Python project template with unit tests, code coverage, linting, type checking, Makefile wrapper, and GitHub Actions.☆143Updated 7 months ago
- Kedro Plugin to support running workflows on Kubeflow Pipelines☆53Updated 2 months ago
- Learn how to create reliable ML systems by testing code, data and models.☆83Updated 2 years ago
- ☆16Updated last year
- Feast AWS guide using Redshift / Spectrum / DynamoDB to build a credit scoring model☆61Updated 3 years ago
- Data search & enrichment library for Machine Learning → Easily find and add relevant features to your ML & AI pipeline from hundreds of p…☆319Updated last week
- Plugins, extensions, case studies, articles, and video tutorials for Kedro☆64Updated last month
- Demo for CI/CD in a machine learning project☆93Updated last year
- Free Open-source ML observability course for data scientists and ML engineers. Learn how to monitor and debug your ML models in productio…☆70Updated 11 months ago
- Using a feature store to connect the DataOps and MLOps workflows to enable collaborative teams to develop efficiently.☆54Updated 2 years ago
- Learn how to monitor ML systems to identify and mitigate sources of drift before model performance decay.☆76Updated 2 years ago
- ⚓ Eurybia monitors model drift over time and securizes model deployment with data validation☆205Updated 3 weeks ago
- Templates for your Kedro projects.☆67Updated this week
- End to End example integrating MLFlow and Seldon Core☆51Updated 4 years ago
- Joining the modern data stack with the modern ML stack☆193Updated last year
- Deploy A/B testing infrastructure in a containerized microservice architecture for Machine Learning applications.☆39Updated last year
- 🧪 Simple data science experimentation & tracking with jupyter, papermill, and mlflow.☆174Updated 4 months ago
- Example repo to kickstart integration with mlflow recipes.☆37Updated 2 months ago
- Find data quality issues and clean your data in a single line of code with a Scikit-Learn compatible Transformer.☆127Updated 11 months ago
- A MLOps platform using prefect, mlflow, FastAPI, Prometheus/Grafana und streamlit☆74Updated 2 years ago
- Recommendations at "Reasonable Scale": joining dataOps with recSys through dbt, Merlin and Metaflow☆230Updated last year
- 🚀 Stream inferences of real-time ML models in production to any data lake (Experimental)☆78Updated 2 years ago