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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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Pre-training genomic language models using AWS HealthOmics and Amazon SageMaker

AWS Machine Learning

In this blog post and open source project , we show you how you can pre-train a genomics language model, HyenaDNA , using your genomic data in the AWS Cloud. Solution overview In this blog post we address pre-training a genomic language model on an assembled genome. e-]*)"}, {"Name": "eval_loss", "Regex": "Eval Average Loss: ([0-9.e-]*)"},

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Testing times: testingRTC is the smart, synchronized, real-world scenario WebRTC testing solution for the times we live in.

Spearline

Consequently, no other testing solution can provide the range and depth of testing metrics and analytics. And testingRTC offers multiple ways to export these metrics, from direct collection from webhooks, to downloading results in CSV format using the REST API. Happy days! You can check framerate information for video here too.

Scripts 98
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Build an image search engine with Amazon Kendra and Amazon Rekognition

AWS Machine Learning

Using architecture diagrams as an example, the solution needs to search through reference links and technical documents for architecture diagrams and identify the services present. With Amazon Kendra, you can search for results, such as images or documents, that have been indexed.

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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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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.