eugeneyan / ml-design-docs
π Design doc template & examples for machine learning systems (requirements, methodology, implementation, etc.)
β571Updated last year
Alternatives and similar repositories for ml-design-docs:
Users that are interested in ml-design-docs are comparing it to the libraries listed below
- π Minimal examples of machine learning tests for implementation, behaviour, and performance.β258Updated 2 years ago
- Software Architecture for ML engineersβ393Updated 2 years ago
- The Fuzzy Labs guide to the universe of open source MLOpsβ452Updated 6 months ago
- An end-to-end implementation of intent prediction with Metaflow and other cool toolsβ853Updated last year
- π§ͺ Simple data science experimentation & tracking with jupyter, papermill, and mlflow.β177Updated 6 months ago
- π Python project template with unit tests, code coverage, linting, type checking, Makefile wrapper, and GitHub Actions.β145Updated 9 months ago
- Toy example of an applied ML pipeline for me to experiment with MLOps tools.β207Updated 3 years ago
- Recommendations at "Reasonable Scale": joining dataOps with recSys through dbt, Merlin and Metaflowβ234Updated last year
- π Papers, guides, and mentor interviews on applying machine learning for ApplyingML.comβthe ghost knowledge of machine learning.β197Updated 7 months ago
- A series of Terraform based recipes to provision popular MLOps stacks on the cloud.β254Updated 3 months ago
- The purpose of the catalog is to help data science teams to collect all the requirements to consider while building a ML model and producβ¦β128Updated 4 years ago
- Behavioral "black-box" testing for recommender systemsβ464Updated last year
- An ongoing list of pandas quirksβ950Updated last year
- Collection of articles listing reasons why data science projects fail.β460Updated 3 years ago
- Compare MLOps Platforms. Breakdowns of SageMaker, VertexAI, AzureML, Dataiku, Databricks, h2o, kubeflow, mlflow...β389Updated 2 years ago
- πΆ A tool to package, serve, and deploy any ML model on any platform. Archived to be resurrected one dayπ€β720Updated last year
- π€ A curated awesome list of Machine Learning Engineering resources. Feel free to contribute!β268Updated 2 months ago
- Template repository for data science lifecycle projectβ183Updated 4 years ago
- CDF SIG MLOpsβ609Updated last month
- 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
- Host repository for the "Reproducible Deep Learning" PhD courseβ403Updated 2 years ago
- Kaggle Pipeline for tabular data competitionsβ204Updated 6 months ago
- Doubt your data, find bad labels.β508Updated 6 months ago
- A Collection of GitHub Actions That Facilitate MLOpsβ207Updated 2 years ago
- Curated list of open source tooling for data-centric AI on unstructured data.β705Updated last year
- This repository aims to map the ecosystem of artificial intelligence guidelines, principles, codes of ethics, standards, regulation and bβ¦β1,287Updated 2 weeks ago
- A toolkit that streamlines and automates the generation of model cardsβ427Updated last year
- π Simple recommender with matrix factorization, graph, and NLP. Beating the regular collaborative filtering baseline.β137Updated 6 months ago
- The Data Science Lifecycle Process is a process for taking data science teams from Idea to Value repeatedly and sustainably. The process β¦β497Updated 3 years ago
- β705Updated 2 years ago