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Why Software Engineers Should Be Embracing AI: A Guide to Staying Ahead

ODSC - Open Data Science

The rapid evolution of AI is transforming nearly every industry/domain, and software engineering is no exception. But how so with software engineering you may ask? These technologies are helping engineers accelerate development, improve software quality, and streamline processes, just to name a few.

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Machine Learning Operations (MLOPs) with Azure Machine Learning

ODSC - Open Data Science

Data Estate: This element represents the organizational data estate, potential data sources, and targets for a data science project. Data Engineers would be the primary owners of this element of the MLOps v2 lifecycle. The Azure data platforms in this diagram are neither exhaustive nor prescriptive.

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Learnings From Building the ML Platform at Stitch Fix

The MLOps Blog

This is Piotr Niedźwiedź and Aurimas GriciÅ«nas from neptune.ai , and you’re listening to ML Platform Podcast. Stefan is a software engineer, data scientist, and has been doing work as an ML engineer. As you’ve been running the ML data platform team, how do you do that?

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Learnings From Building the ML Platform at Mailchimp

The MLOps Blog

I started from tech, my first job was an internship at Google as a software engineer. I’m from Poland, and I remember when I got an offer from Google to join as a regular software engineer. I switched from analytics to data science, then to machine learning, then to data engineering, then to MLOps.

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Definite Guide to Building a Machine Learning Platform

The MLOps Blog

Automation You want the ML models to keep running in a healthy state without the data scientists incurring much overhead in moving them across the different lifecycle phases. It would make sure that all development and deployment workflows use good software engineering practices. My Story DevOps Engineers Who they are?