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Use LangChain with PySpark to process documents at massive scale with Amazon SageMaker Studio and Amazon EMR Serverless

AWS Machine Learning

Harnessing the power of big data has become increasingly critical for businesses looking to gain a competitive edge. However, managing the complex infrastructure required for big data workloads has traditionally been a significant challenge, often requiring specialized expertise.

Big data 116
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Intelligent document processing with AWS AI services: Part 2

AWS Machine Learning

Amazon’s intelligent document processing (IDP) helps you speed up your business decision cycles and reduce costs. Across multiple industries, customers need to process millions of documents per year in the course of their business. The following figure shows the stages that are typically part of an IDP workflow.

Banking 98
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Create a generative AI–powered custom Google Chat application using Amazon Bedrock

AWS Machine Learning

AWS offers powerful generative AI services , including Amazon Bedrock , which allows organizations to create tailored use cases such as AI chat-based assistants that give answers based on knowledge contained in the customers’ documents, and much more. The following figure illustrates the high-level design of the solution.

APIs 121
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Intelligent document processing with AWS AI and Analytics services in the insurance industry: Part 2

AWS Machine Learning

In Part 1 of this series, we discussed intelligent document processing (IDP), and how IDP can accelerate claims processing use cases in the insurance industry. We discussed how we can use AWS AI services to accurately categorize claims documents along with supporting documents. Part 1: Classification and extraction of documents.

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Deploy a Slack gateway for Amazon Bedrock

AWS Machine Learning

Imagine the possibilities: Quick and efficient brainstorming sessions, real-time ideation, and even drafting documents or code snippets—all powered by the latest advancements in AI. The Slack application sends the event to Amazon API Gateway , which is used in the event subscription.

APIs 105
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Build a custom UI for Amazon Q Business

AWS Machine Learning

This solution uses an Amazon Cognito user pool as an OAuth-compatible identity provider (IdP), which is required in order to exchange a token with AWS IAM Identity Center and later on interact with the Amazon Q Business APIs. Amazon Q uses the chat_sync API to carry out the conversation. A VPC where you will deploy the solution.

APIs 136
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Use Amazon SageMaker Model Card sharing to improve model governance

AWS Machine Learning

One of the tools available as part of the ML governance is Amazon SageMaker Model Cards , which has the capability to create a single source of truth for model information by centralizing and standardizing documentation throughout the model lifecycle. They provide a fact sheet of the model that is important for model governance.