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­­Speed ML development using SageMaker Feature Store and Apache Iceberg offline store compaction

AWS Machine Learning

The offline store data is stored in an Amazon Simple Storage Service (Amazon S3) bucket in your AWS account. A new optional parameter TableFormat can be set either interactively using Amazon SageMaker Studio or through code using the API or the SDK. put_record API to ingest individual records or to handle streaming sources.

Scripts 73
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Generative AI and multi-modal agents in AWS: The key to unlocking new value in financial markets

AWS Machine Learning

Large language models – The large language models (LLMs) are available via Amazon Bedrock, SageMaker JumpStart, or an API. Prerequisites To run this solution, you must have an API key to an LLM such as Anthropic Claude v2, or have access to Amazon Bedrock foundation models. Data exploration on stock data is done using Athena.

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Automate caption creation and search for images at enterprise scale using generative AI and Amazon Kendra

AWS Machine Learning

We demonstrate CDE using simple examples and provide a step-by-step guide for you to experience CDE in an Amazon Kendra index in your own AWS account. After ingestion, images can be searched via the Amazon Kendra search console, API, or SDK. However, we can use CDE for a wider range of use cases.

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Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs

AWS Machine Learning

In addition to awareness, your teams should take action to account for generative AI in governance, assurance, and compliance validation practices. You should begin by extending your existing security, assurance, compliance, and development programs to account for generative AI.

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FMOps/LLMOps: Operationalize generative AI and differences with MLOps

AWS Machine Learning

Each business unit has each own set of development (automated model training and building), preproduction (automatic testing), and production (model deployment and serving) accounts to productionize ML use cases, which retrieve data from a centralized or decentralized data lake or data mesh, respectively.

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Identify key insights from text documents through fine-tuning and HPO with Amazon SageMaker JumpStart

AWS Machine Learning

Organizations across industries such as retail, banking, finance, healthcare, manufacturing, and lending often have to deal with vast amounts of unstructured text documents coming from various sources, such as news, blogs, product reviews, customer support channels, and social media. Healthcare and life sciences. Fraud detection.

Scripts 72
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Face-off Probability, part of NHL Edge IQ: Predicting face-off winners in real time during televised games

AWS Machine Learning

Apache Flink is a distributed streaming, high-throughput, low-latency data flow engine that provides a convenient and easy way to use the Data Stream API, and it supports stateful processing functions, checkpointing, and parallel processing out of the box. Yash Shah is a Science Manager in the Amazon ML Solutions Lab. Erick Martinez is a Sr.