visenger / Awesome-ML-Model-Governance
This repository provides a curated list of references about Machine Learning Model Governance, Ethics, and Responsible AI.
β100Updated 7 months ago
Related projects β
Alternatives and complementary repositories for Awesome-ML-Model-Governance
- π Python project template with unit tests, code coverage, linting, type checking, Makefile wrapper, and GitHub Actions.β143Updated 7 months ago
- A curated list of awesome academic research, books, code of ethics, data sets, institutes, newsletters, principles, podcasts, reports, toβ¦β55Updated this week
- π Minimal examples of machine learning tests for implementation, behaviour, and performance.β254Updated 2 years ago
- A collection of machine learning model cards and datasheets.β71Updated 5 months ago
- Example project with a complete MLOps cycle: versioning data, generating reports on pull requests and deploying the model on releases witβ¦β45Updated 2 years ago
- Materials for my 2021 NYU class on NLP and ML Systems (Master of Engineering).β96Updated last year
- ML project template facilitating both research and production phases.β102Updated 5 years ago
- The Fuzzy Labs guide to the universe of open source MLOpsβ449Updated 4 months ago
- Metaflow tutorials for ODSC West 2021β65Updated 3 years ago
- Responsible AI knowledge baseβ98Updated last year
- Learn how to create reliable ML systems by testing code, data and models.β83Updated 2 years ago
- A PaaS End-to-End ML Setup with Metaflow, Serverless and SageMaker.β37Updated 3 years ago
- Learn how to monitor ML systems to identify and mitigate sources of drift before model performance decay.β76Updated 2 years ago
- A repository that showcases how you can use ZenML with Gitβ65Updated 3 months ago
- Interview Questions and Answers for Machine Learning Engineer roleβ119Updated last year
- A toolkit that streamlines and automates the generation of model cardsβ426Updated last year
- Using a feature store to connect the DataOps and MLOps workflows to enable collaborative teams to develop efficiently.β54Updated 2 years ago
- A repository for all ZenML projects that are specific production use-cases.β217Updated last week
- π Material for PyData Global 2021 Presentation: Effective Testing for Machine Learning Projectsβ81Updated 2 years ago
- Joining the modern data stack with the modern ML stackβ193Updated last year
- Free Open-source ML observability course for data scientists and ML engineers. Learn how to monitor and debug your ML models in productioβ¦β70Updated 11 months ago
- π§ͺ Simple data science experimentation & tracking with jupyter, papermill, and mlflow.β174Updated 4 months ago
- Quick demo of setting up a deep learning Python environment using conda and pip-tools.β38Updated 3 years ago
- π Papers, guides, and mentor interviews on applying machine learning for ApplyingML.comβthe ghost knowledge of machine learning.β191Updated 5 months ago
- Toy example of an applied ML pipeline for me to experiment with MLOps tools.β206Updated 2 years ago
- A curated list of awesome open source tools and commercial products for monitoring data quality, monitoring model performance, and profilβ¦β64Updated 6 months ago
- Curriculum and roadmap from 0 to Mastery for MLOps. Adding value to your machine learning model by deploying it for people to use it to sβ¦β184Updated 2 years ago
- Template repository for data science lifecycle projectβ180Updated 4 years ago
- Materials for workshops on the Hugging Face ecosystemβ150Updated last year
- Demo for CI/CD in a machine learning projectβ93Updated last year