Machine learning operations (mlops) is the union of data engineering, machine learning, and devops.
Beginner to pro guide.
This document is for data scientists and ml engineers who want to apply devops principles to ml systems (mlops).
Mlops or ml ops is a paradigm that aims to deploy and maintain machine learning models in production reliably and efficiently.
The objective of an mlops team is to automate the deployment of ml models into the core software system or as a service.
Mlops, short for machine learning operations, is a set of practices designed to create an assembly line for building.
Mlops is a discipline focused on the deployment, testing, monitoring, and automation of ml systems in production.
Mlops is a set of practices that combines machine learning, software engineering, and devops to manage the entire. For those seeking similar resources, our guide on How To Establish Best Practices For Cloud Monitoring.pdf offers a detailed breakdown on this subject.
