awesome-mlops / awesome-ml-monitoringLinks
A curated list of awesome open source tools and commercial products for monitoring data quality, monitoring model performance, and profiling data π
β85Updated last year
Alternatives and similar repositories for awesome-ml-monitoring
Users that are interested in awesome-ml-monitoring are comparing it to the libraries listed below
Sorting:
- A series of Terraform based recipes to provision popular MLOps stacks on the cloud.β255Updated 11 months ago
- A repository that showcases how you can use ZenML with Gitβ69Updated last month
- Construct a modern data stack and orchestration the workflows to create high quality data for analytics and ML applications.β226Updated 3 years ago
- MLOps Cookiecutter Template: A Base Project Structure for Secure Production ML Engineeringβ42Updated 10 months ago
- Example project with a complete MLOps cycle: versioning data, generating reports on pull requests and deploying the model on releases witβ¦β48Updated 3 years ago
- Data search & enrichment library for Machine Learning β Easily find and add relevant features to your ML & AI pipeline from hundreds of pβ¦β338Updated this week
- Free Open-source ML observability course for data scientists and ML engineers. Learn how to monitor and debug your ML models in productioβ¦β95Updated last year
- Demo for CI/CD in a machine learning projectβ111Updated 2 years ago
- π§ͺ Simple data science experimentation & tracking with jupyter, papermill, and mlflow.β182Updated last year
- π Minimal examples of machine learning tests for implementation, behaviour, and performance.β263Updated 2 years ago
- End to End example integrating MLFlow and Seldon Coreβ52Updated 4 years ago
- β Eurybia monitors model drift over time and securizes model deployment with data validationβ213Updated 10 months ago
- Joining the modern data stack with the modern ML stackβ199Updated 2 years ago
- Using a feature store to connect the DataOps and MLOps workflows to enable collaborative teams to develop efficiently.β57Updated 3 years ago
- Learn how to monitor ML systems to identify and mitigate sources of drift before model performance decay.β91Updated 3 years ago
- A simple guide to MLOps through ZenML and its various integrations.β187Updated last year
- π² A curated list of MLOps projects, tools and resourcesβ185Updated last year
- MLOps maturity assessmentβ61Updated 2 years ago
- π Python project template with unit tests, code coverage, linting, type checking, Makefile wrapper, and GitHub Actions.β148Updated last year
- A repository for all ZenML projects that are specific production use-cases.β276Updated 2 weeks ago
- Practical Deep Learning at Scale with MLFlow, published by Packtβ162Updated last week
- Fetch, transform and plot real-time OHLC data from Coinbase using Bytewax, Bokeh and Streamlitβ129Updated last year
- Examples of using Evidently to evaluate, test and monitor ML models.β39Updated last month
- Recommendations at "Reasonable Scale": joining dataOps with recSys through dbt, Merlin and Metaflowβ239Updated 2 years ago
- Template repo for kickstarting recipes for regression use caseβ54Updated 9 months ago
- The Fuzzy Labs guide to the universe of open source MLOpsβ472Updated 3 months ago
- Official code repo for the O'Reilly Book - Machine Learning for High-Risk Applicationsβ102Updated 2 years ago
- An example MLFlow projectβ48Updated 8 months ago
- Streamline scikit-learn model comparison.β143Updated 2 years ago
- Open-Source Software, Tutorials, and Research on Data-Centric AI π€β339Updated last year