awesome-mlops
by visenger
A curated list of references for MLOps
AI summary
ML project guidance
A curated collection of resources and guides for managing machine learning projects from design to deployment
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- 505
What's in the list
505 links in 19 sections, with live GitHub stats.activeno commit in 2y
MLOps Core
MLOps SIG Specification
Awesome production machine learning: State of MLOps Tools and Frameworks
IBM ML Operationalization Starter Kit
MLOps maturity assessmentMLOps Communities
CDF Special Interest Group - MLOpsMLOps Courses
MLOps Zoomcamp (free)MLOps Books
Links
- The 2021 State of Enterprise Machine Learning
| State of Enterprise ML 2020: and
- Part 1
Back to the Machine Learning fundamentals: How to write code for Model deployment. , ,
- Part 1
Continuous Machine Learning. , . Part 3 is coming soon
Reproducible ML
A Guide to Production Level Deep Learning
Deep Learning in Production (references about deploying deep learning-based models in production)
Deployment & Explainability of Machine Learning COVID-19 Solutions at Scale with Seldon Core and Alibi
Data Science Lifecycle Repository Template
Template: code and pipeline definition for a machine learning project demonstrating how to automate an end to end ML/AI workflow.
Software Engineering for AI/ML - An Annotated Bibliography
ML Engineering on Google Cloud Platform (hands-on labs and code samples)
Awesome Software Engineering for Machine Learning (GitHub repository)
Example code for a basic ML Platform based on Pulumi, FastAPI, DVC, MLFlow and more
MLOps-Basics (GitHub repo)MLOps: Workflow Management
MLOps: Feature Stores
Hopsworks: Data-Intensive AI with a Feature Store
Feast: An open-source Feature Store for Machine LearningMLOps: Data Engineering (DataOps)
- Part 1
Data Quality at Airbnb |
A complete picture of the modern data engineering landscape
A curated list of awesome pipeline toolkitsMLOps: Model Deployment and Serving
- Part 1
ML Model Rollout To Production. |
MLOps: Testing, Monitoring and Maintenance
- Part 1
Test-Driven Development in MLOps
MLOps: Infrastructure & Tooling
- Part 1 — Production ML — The Final Stage of the Model Workflow
ML Infrastructure Tools for Production | |
Talks About MLOps
- An introduction to MLOps on Google Cloud
(First 19 min are vendor-, language-, and framework-agnostic. @visenger)
Existing ML Systems
Papers & tech blogs by companies sharing their work on data science & machine learning in production. By Eugen YanMachine Learning
Awesome TensorFlow
Machine Learning and Data Science Applications in Industry
Examples of techniques for training interpretable machine learning (ML) models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.
Awesome Data Science
Data Science Collected Resources (GitHub repository)
Machine learning cheat sheet
A resource list for causality in statistics, data science and physics
Machine Learning for Beginners - A CurriculumSoftware Engineering
Clean Code concepts adapted for machine learning and data science.
The Book of Secret KnowledgeProduct Management for ML/AI
The Economics of ML/AI
Collection of articles listing reasons why data science projects failMLOps: People & Processes
The Knowledge Repo project is focused on facilitating the sharing of knowledge between data scientists and other technical roles.Newsletters About MLOps, Machine Learning, Data Science and Co.
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