Flipboard

NOVEMBER 24, 2023

JuMa is a service of BMW Group’s AI platform for its data analysts, ML engineers, and data scientists that provides a user-friendly workspace with an integrated development environment (IDE). It is powered by Amazon SageMaker Studio and provides JupyterLab for Python and Posit Workbench for R.

ML 152

ML DevOps Data Scientist ML Engineer 152

AWS Machine Learning Blog

OCTOBER 3, 2024

This approach led to data scientists spending more than 50% of their time on operational tasks, leaving little room for innovation, and posed challenges in monitoring model performance in production. Snowflake is the preferred data platform, and it receives data from Step Functions state machine runs through Amazon CloudWatch logs.

DevOps 83

DevOps Data Science Data Scientist ML 83

ODSC - Open Data Science

JULY 19, 2023

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.

Machine Learning 52

Machine Learning Data Drift Data Science Data Scientist 52

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. You could almost think of Hamilton as DBT for Python functions. It gives a very opinionary way of writing Python.

ML 52

ML Data Scientist Software Engineer Machine Learning 52

The MLOps Blog

OCTOBER 3, 2023

I actually did not pick up Python until about a year before I made the transition to a data scientist role. I switched from analytics to data science, then to machine learning, then to data engineering, then to MLOps. You shifted straight from data science, if I understand correctly. It’s two things.

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

AWS Machine Learning Blog

DECEMBER 18, 2024

One popular library for implementing distributed training is DeepSpeed, a Python optimization library that handles distributed training and makes it memory-efficient and fast by enabling both data and model parallelization. He has expertise in AWS cloud services, DevOps practices, security, data analytics and generative AI.

Large Language Models 90

Large Language Models Data Scarcity LLM Generative AI 90