MLOps: Continuous delivery and automation pipelines in machine learning
Last updated: 2022-11-22 Tuesday
MLOps: Continuous delivery and automation pipelines in machine learning
Continuous delivery and automation pipelines in machine learning by google discusses techniques for implementing machine learning and describes automating continuous integration (CI), continuous delivery (CD), and continuous training (CT) for machine learning (ML) systems.
This document is for data scientists and ML engineers who want to apply DevOps principles to ML systems (MLOps). MLOps is an ML engineering culture and practice that aims at unifying ML system development (Dev) and ML system operation (Ops). Practicing MLOps means that you advocate for automation and monitoring at all steps of ML system construction, including integration, testing, releasing, deployment and infrastructure management.
what is it about
- MLOps level 0: Manual process
- MLOps level 1: ML pipeline automation
- MLOps level 2: CI/CD pipeline automation
what do I think about it
This is a very good mlops practice paper. This is a nice recommondation for starters in mlops