Flipboard

NOVEMBER 24, 2023

With that, the need for data scientists and machine learning (ML) engineers has grown significantly. Data scientists and ML engineers require capable tooling and sufficient compute for their work. It is powered by Amazon SageMaker Studio and provides JupyterLab for Python and Posit Workbench for R.

ML 151

ML DevOps Data Scientist ML Engineer 151

ODSC - Open Data Science

DECEMBER 7, 2023

We’ll also discuss some of the benefits of using set union(), and we’ll see why it’s a popular tool for Python developers. How to Build a 5-Layer Data Stack Spinning up a data platform doesn’t have to be complicated. Here are the 5 must-have layers to drive data product adoption at scale.

Data Scientist 98

Data Scientist Explainable AI Data Science Python 98

Snorkel AI

MAY 26, 2023

[link] Ahmad Khan, head of artificial intelligence and machine learning strategy at Snowflake gave a presentation entitled “Scalable SQL + Python ML Pipelines in the Cloud” about his company’s Snowpark service at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. Welcome everybody.

ML 52

ML Python Machine Learning Data Scientist 52

Snorkel AI

MAY 26, 2023

[link] Ahmad Khan, head of artificial intelligence and machine learning strategy at Snowflake gave a presentation entitled “Scalable SQL + Python ML Pipelines in the Cloud” about his company’s Snowpark service at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. Welcome everybody.

ML 52

ML Python Machine Learning Data Scientist 52

The MLOps Blog

JANUARY 26, 2024

We’ll see how this architecture applies to different classes of ML systems, discuss MLOps and testing aspects, and look at some example implementations. Understanding machine learning pipelines Machine learning (ML) pipelines are a key component of ML systems. But what is an ML pipeline?

Machine Learning 72

Machine Learning Metadata ML Python 72

AWS Machine Learning Blog

SEPTEMBER 18, 2023

SageMaker geospatial capabilities make it easy for data scientists and machine learning (ML) engineers to build, train, and deploy models using geospatial data. The results of SUEWS are then visualized, in this case with Arup’s existing geospatial data platform.

Data Scientist 120

Data Scientist ML Machine Learning ML Engineer 120

ODSC - Open Data Science

JULY 19, 2023

Machine Learning Operations (MLOps) can significantly accelerate how data scientists and ML engineers meet organizational needs. A well-implemented MLOps process not only expedites the transition from testing to production but also offers ownership, lineage, and historical data about ML artifacts used within the team.

Machine Learning 52

Machine Learning Data Drift Data Science Data Scientist 52