DataRobot Blog

MARCH 16, 2023

An AI platform that works well with a broad enterprise ecosystem: A platform that seamlessly integrates with the substantial investments businesses have already made in infrastructure, practitioner tools, data platforms and business applications.

AI 98

AI AI DevOps Neural Network 98

AWS Machine Learning Blog

OCTOBER 20, 2023

The architecture maps the different capabilities of the ML platform to AWS accounts. The functional architecture with different capabilities is implemented using a number of AWS services, including AWS Organizations , SageMaker, AWS DevOps services, and a data lake.

ML 119

ML Data Scientist ML Engineer Data Science 119

The MLOps Blog

AUGUST 3, 2023

Stefan is a software engineer, data scientist, and has been doing work as an ML engineer. He also ran the data platform in his previous company and is also co-creator of open-source framework, Hamilton. As you’ve been running the ML data platform team, how do you do that? Stefan: Yeah. Thanks for having me.

ML 52

ML Data Scientist Software Engineer Machine Learning 52

The MLOps Blog

OCTOBER 3, 2023

I switched from analytics to data science, then to machine learning, then to data engineering, then to MLOps. For me, it was a little bit of a longer journey because I kind of had data engineering and cloud engineering and DevOps engineering in between. You shifted straight from data science, if I understand correctly.

ML 52

ML Data Scientist Machine Learning Data Science 52

The MLOps Blog

MARCH 21, 2023

To make that possible, your data scientists would need to store enough details about the environment the model was created in and the related metadata so that the model could be recreated with the same or similar outcomes. You need to build your ML platform with experimentation and general workflow reproducibility in mind.

Machine Learning 69

Machine Learning Data Scientist ML Metadata 69