IBM Journey to AI blog

SEPTEMBER 20, 2023

These include data ingestion, data selection, data pre-processing, FM pre-training, model tuning to one or more downstream tasks, inference serving, and data and AI model governance and lifecycle management—all of which can be described as FMOps. IBM watsonx consists of the following: IBM watsonx.ai

Large Language Models 238

Large Language Models DevOps Data Science AI Modeling 238

AWS Machine Learning Blog

FEBRUARY 27, 2024

Axfood has a structure with multiple decentralized data science teams with different areas of responsibility. Together with a central data platform team, the data science teams bring innovation and digital transformation through AI and ML solutions to the organization.

Machine Learning 137

Machine Learning DevOps Data Scientist Data Quality 137

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 133

ML Data Scientist ML Engineer Data Science 133

Marktechpost

JULY 17, 2023

The company’s H20 Driverless AI streamlines AI development and predictive analytics for professionals and citizen data scientists through open source and customized recipes. The platform makes collaborative data science better for corporate users and simplifies predictive analytics for professional data scientists.

Machine Learning 98

Machine Learning Data Mining Data Scientist Data Science 98

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

” — Isaac Vidas , Shopify’s ML Platform Lead, at Ray Summit 2022 Monitoring Monitoring is an essential DevOps practice, and MLOps should be no different. Checking at intervals to make sure that model performance isn’t degrading in production is a good MLOps practice for both teams and platforms.

Machine Learning 69

Machine Learning Data Scientist ML Metadata 69