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Build an AI-powered document processing platform with open source NER model and LLM on Amazon SageMaker

Flipboard

This endpoint based architecture provides decoupling between the other processing, allowing independent scaling, versioning, and maintenance of each component. The decoupled nature of the endpoints also provides flexibility to update or replace individual models without impacting the broader system architecture.

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Real value, real time: Production AI with Amazon SageMaker and Tecton

AWS Machine Learning Blog

In a fraud detection system, when someone makes a transaction (such as buying something online), your app might follow these steps: It checks with other services to get more information (for example, “Is this merchant known to be risky?”) This process is shown in the following diagram.

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9 Careers You Could Go into With a Data Science Degree

Smart Data Collective

Data Engineer. In this role, you would perform batch processing or real-time processing on data that has been collected and stored. As a data engineer, you could also build and maintain data pipelines that create an interconnected data ecosystem that makes information available to data scientists.

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Data Intelligence empowers informed decisions

Pickl AI

In the realm of Data Intelligence, the blog demystifies its significance, components, and distinctions from Data Information, Artificial Intelligence, and Data Analysis. Data Intelligence emerges as the indispensable force steering businesses towards informed and strategic decision-making. These insights?

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Build an Amazon SageMaker Model Registry approval and promotion workflow with human intervention

AWS Machine Learning Blog

Specialist Data Engineering at Merck, and Prabakaran Mathaiyan, Sr. ML Engineer at Tiger Analytics. The model detail information is stored in Parameter Store, including the model version, approved target environment, and model package. This post is co-written with Jayadeep Pabbisetty, Sr.

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Accelerate machine learning time to value with Amazon SageMaker JumpStart and PwC’s MLOps accelerator

AWS Machine Learning Blog

With a comprehensive suite of technical artifacts, including infrastructure as code (IaC) scripts, data processing workflows, service integration code, and pipeline configuration templates, PwC’s MLOps accelerator simplifies the process of developing and operating production-class prediction systems.

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Innovating at speed: BMW’s generative AI solution for cloud incident analysis

AWS Machine Learning Blog

It requires checking many systems and teams, many of which might be failing, because theyre interdependent. Developers need to reason about the system architecture, form hypotheses, and follow the chain of components until they have located the one that is the culprit.

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