AWS Machine Learning Blog

OCTOBER 20, 2023

This framework considers multiple personas and services to govern the ML lifecycle at scale. Data scientists search and pull features from the central feature store catalog, build models through experiments, and select the best model for promotion.

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ML Data Scientist ML Engineer Data Science 101

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. JuMa is now available to all data scientists, ML engineers, and data analysts at BMW Group.

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ML DevOps Data Scientist ML Engineer 95

DataRobot Blog

SEPTEMBER 13, 2022

What Do Data Scientists Do? Data scientists drive business outcomes. Many implement machine learning and artificial intelligence to tackle challenges in the age of Big Data. What data scientists do is directly tied to an organization’s AI maturity level. BARC ANALYST REPORT. Download Now. Operationalization.

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Data Scientist Automation ML Data Ingestion 52

AWS Machine Learning Blog

JUNE 26, 2023

This addresses a critical obstacle to wider adoption because ML administrators can now automate their tasks programmatically. With the power of the AWS CDK, ML administrators can streamline workflows, reduce manual efforts, and ensure consistency in managing permissions for their ML infrastructure.

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ML Data Scientist Automation Machine Learning 71

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 ML Engineer 52

The MLOps Blog

JUNE 27, 2023

This includes features for hyperparameter tuning, automated model selection, and visualization of model metrics. They should also offer version control capabilities to manage the changes and revisions of ML artifacts, ensuring reproducibility and facilitating effective teamwork.

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Machine Learning Metadata Data Quality Data Scientist 134

AWS Machine Learning Blog

JANUARY 6, 2023

Jessie Danqing Cai, Associate Research Director, Big Data & Analytics Practice, IDC Asia/Pacific. AWS continues to offer the best notebook experience for users, with the launch of three new features that help you coordinate and automate notebook code.

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Data Scientist ML Machine Learning Explainability 69

AWS Machine Learning Blog

AUGUST 31, 2023

Implementing these guardrails is getting harder for enterprises because the ML processes and activities within enterprises are becoming more complex due to the inclusion of deeply involved processes that require contributions from multiple stakeholders and personas. Ram Vittal is a Principal ML Solutions Architect at AWS.

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ML Data Scientist Machine Learning Automation 91

Flipboard

MARCH 7, 2023

The main benefits of this approach are a high level of version control and reproducibility of an ML runtime environment and immediate availability of library packages because they’re installed in the image. You can implement comprehensive tests, governance, security guardrails, and CI/CD automation to produce custom app images.

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Python Automation Data Scientist ML 93

Snorkel AI

JULY 5, 2023

We thought we’d structure this more as a conversation where we walk you through some of our thinking around some of the most common themes in data centricity in applied AI. Is more data always better? And the important thing here is really the predictive signal in the data. Maybe I’ll start us off here Robert?

Large Language Models 52

Large Language Models Metadata AI AI 52

Snorkel AI

JULY 5, 2023

We thought we’d structure this more as a conversation where we walk you through some of our thinking around some of the most common themes in data centricity in applied AI. Is more data always better? And the important thing here is really the predictive signal in the data. Maybe I’ll start us off here Robert?

Large Language Models 52

Large Language Models Metadata AI AI 52

AWS Machine Learning Blog

AUGUST 31, 2023

Implementing these guardrails is getting harder for enterprises because the ML processes and activities within enterprises are becoming more complex due to the inclusion of deeply involved processes that require contributions from multiple stakeholders and personas. Ram Vittal is a Principal ML Solutions Architect at AWS.

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ML Data Scientist Machine Learning Automation 52

AWS Machine Learning Blog

APRIL 19, 2023

Our automated Kinesis Data Analytics for Apache Flink aggregation takes over from there, maintaining a near-real-time view of transaction counts and amounts in Feature Store, with a sliding 10-minute lookback window. sagemaker_runtime = boto3.client(service_name='runtime.sagemaker')

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ML Data Scientist Big Data Machine Learning 77

Snorkel AI

MAY 24, 2023

From generative modeling to automated product tagging, cloud computing, predictive analytics, and deep learning, the speakers present a diverse range of expertise. Our speakers lead their fields and embody the desire to create revolutionary ML experiences by leveraging the power of data-centric AI to drive innovation and progress.

Machine Learning 52

Machine Learning Data Scientist Computer Vision ML 52

Snorkel AI

MAY 24, 2023

From generative modeling to automated product tagging, cloud computing, predictive analytics, and deep learning, the speakers present a diverse range of expertise. Our speakers lead their fields and embody the desire to create revolutionary ML experiences by leveraging the power of data-centric AI to drive innovation and progress.

Machine Learning 52

Machine Learning Data Scientist Computer Vision ML 52