AWS Machine Learning Blog

AUGUST 4, 2023

As a result, businesses can accelerate time to market while maintaining data integrity and security, and reduce the operational burden of moving data from one location to another. With Einstein Studio, a gateway to AI tools on the data platform, admins and data scientists can effortlessly create models with a few clicks or using code.

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Data Scientist ML ETL Data Platform 92

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. UHeat uses a combination of satellite imagery and open-source climate data to perform the analysis. This now takes a matter of hours with SageMaker.

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Data Scientist ML Machine Learning ML Engineer 123

The MLOps Blog

MARCH 21, 2023

From gathering and processing data to building models through experiments, deploying the best ones, and managing them at scale for continuous value in production—it’s a lot. As the number of ML-powered apps and services grows, it gets overwhelming for data scientists and ML engineers to build and deploy models at scale.

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Machine Learning Data Scientist ML Metadata 69

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.

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AWS Machine Learning Blog

SEPTEMBER 12, 2024

In fact, 96 percent of all AI/ML unicorns—and 90 percent of the 2024 Forbes AI 50—are AWS customers. We’re empowering data scientists, ML engineers, and other builders with new capabilities that make generative AI development faster, easier, more secure, and less costly.

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Generative AI AI AI ML 96

Snorkel AI

JUNE 9, 2023

Snorkel AI wrapped the second day of our The Future of Data-Centric AI virtual conference by showcasing how Snorkel’s data-centric platform has enabled customers to succeed, taking a deep look at Snorkel Flow’s capabilities, and announcing two new solutions.

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Large Language Models Data Scientist Machine Learning Computer Vision 52

Snorkel AI

JUNE 9, 2023

Snorkel AI wrapped the second day of our The Future of Data-Centric AI virtual conference by showcasing how Snorkel’s data-centric platform has enabled customers to succeed, taking a deep look at Snorkel Flow’s capabilities, and announcing two new solutions.

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Large Language Models Data Scientist Machine Learning Computer Vision 52

The MLOps Blog

OCTOBER 3, 2023

So I tell people honestly, I’ve spent the last eight years working up and down the data and ML value chain effectively – a fancy way of saying “job hopping.” How to transition from data analytics to MLOps engineering Piotr: Miki, you’ve been a data scientist, right? And later, an MLOps engineer.

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ML Data Scientist Machine Learning Data Science 52

Snorkel AI

MAY 26, 2023

And one of the biggest challenges that we see is taking an idea, an experiment, or an ML experiment that data scientists might be running in their notebooks and putting that into production. And so data scientists might be leveraging one compute service and might be leveraging an extracted CSV for their experimentation.

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ML Python Machine Learning Data Scientist 52

Snorkel AI

MAY 26, 2023

And one of the biggest challenges that we see is taking an idea, an experiment, or an ML experiment that data scientists might be running in their notebooks and putting that into production. And so data scientists might be leveraging one compute service and might be leveraging an extracted CSV for their experimentation.

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ML Python Machine Learning Data Scientist 52

The MLOps Blog

AUGUST 3, 2023

This is Piotr Niedźwiedź and Aurimas Griciūnas 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. To a junior data scientist, it doesn’t matter if you’re using Airflow, Prefect , Dexter.

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ML Data Scientist Software Engineer Machine Learning 52