Remove 2010 Remove Analytics Remove Data Pipeline
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Build generative AI applications quickly with Amazon Bedrock IDE in Amazon SageMaker Unified Studio

AWS Machine Learning Blog

Through simple conversations, business teams can use the chat agent to extract valuable insights from both structured and unstructured data sources without writing code or managing complex data pipelines. This will provision the backend infrastructure and services that the sales analytics application will rely on.

AWS 112
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Improving air quality with generative AI

AWS Machine Learning Blog

If useful, it can be further extended to a data lake platform that uses AWS Glue (a serverless data integration service for data preparation) and Amazon Athena (a serverless and interactive analytics service) to analyze and visualize data. She holds 30+ patents and has co-authored 100+ journal/conference papers.

AWS 136
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Boosting RAG-based intelligent document assistants using entity extraction, SQL querying, and agents with Amazon Bedrock

AWS Machine Learning Blog

This is especially true for questions that require analytical reasoning across multiple documents. This task involves answering analytical reasoning questions. In this post, we show how to design an intelligent document assistant capable of answering analytical and multi-step reasoning questions in three parts.

SQL 133
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Unlocking generative AI for enterprises: How SnapLogic powers their low-code Agent Creator using Amazon Bedrock

AWS Machine Learning Blog

Since joining SnapLogic in 2010, Greg has helped design and implement several key platform features including cluster processing, big data processing, the cloud architecture, and machine learning. He currently is working on Generative AI for data integration.

AI 96
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A review of purpose-built accelerators for financial services

AWS Machine Learning Blog

The financial services industry (FSI) is no exception to this, and is a well-established producer and consumer of data and analytics. These activities cover disparate fields such as basic data processing, analytics, and machine learning (ML). The union of advances in hardware and ML has led us to the current day.

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