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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. Extract and analyze data from documents.

Scripts 72
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Build a cross-account MLOps workflow using the Amazon SageMaker model registry

AWS Machine Learning

When designing production CI/CD pipelines, AWS recommends leveraging multiple accounts to isolate resources, contain security threats and simplify billing-and data science pipelines are no different. Some things to note in the preceding architecture: Accounts follow a principle of least privilege to follow security best practices.

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Simplify continuous learning of Amazon Comprehend custom models using Comprehend flywheel

AWS Machine Learning

Amazon Comprehend is a managed AI service that uses natural language processing (NLP) with ready-made intelligence to extract insights about the content of documents. It develops insights by recognizing the entities, key phrases, language, sentiments, and other common elements in a document.

APIs 68
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Build production-ready generative AI applications for enterprise search using Haystack pipelines and Amazon SageMaker JumpStart with LLMs

AWS Machine Learning

This blog post is co-written with Tuana Çelik from deepset. Enterprise search is a critical component of organizational efficiency through document digitization and knowledge management. The Haystack Indexing Pipeline includes the following high-level steps: Upload a document. Initialize DocumentStore and index documents.

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Build a powerful question answering bot with Amazon SageMaker, Amazon OpenSearch Service, Streamlit, and LangChain

AWS Machine Learning

A small number of similar documents (typically three) is added as context along with the user question to the “prompt” provided to another LLM and then that LLM generates an answer to the user question using information provided as context in the prompt. Chunking of knowledge base documents. Implementing the question answering task.

APIs 77
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Using Web Components in a React Application

Nexmo

Vonage API Account. To complete this tutorial, you will need a Vonage API account. Once you have an account, you can find your API Key and API Secret at the top of the Vonage API Dashboard. Web Component polyfill --> <script src="[link]. <!-- ” The documentation has more info and offers alternatives.

APIs 118
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Inbound Call Center Agent Responsibilities and Duties

JustCall

In this blog, we will explore the inbound call center agent duties and understand how to create a solid inbound call agent job description. Documenting calls : In order to ensure that customer information is accurate and up-to-date, agents are responsible for documenting calls in the call center software.