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Reinventing the data experience: Use generative AI and modern data architecture to unlock insights

AWS Machine Learning Blog

The combination of large language models (LLMs), including the ease of integration that Amazon Bedrock offers, and a scalable, domain-oriented data infrastructure positions this as an intelligent method of tapping into the abundant information held in various analytics databases and data lakes.

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Federated Learning on AWS with FedML: Health analytics without sharing sensitive data – Part 1

AWS Machine Learning Blog

In the second post , we present the use cases and dataset to show its effectiveness in analyzing real-world healthcare datasets, such as the eICU data , which comprises a multi-center critical care database collected from over 200 hospitals. Background. Therefore, it brings analytics to data, rather than moving data to analytics.

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A review of purpose-built accelerators for financial services

AWS Machine Learning Blog

These activities cover disparate fields such as basic data processing, analytics, and machine learning (ML). ML is often associated with PBAs, so we start this post with an illustrative figure. The ML paradigm is learning followed by inference. The union of advances in hardware and ML has led us to the current day.

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Using task-specific models from AI21 Labs on AWS

AWS Machine Learning Blog

It streamlines workflows by quickly accessing relevant information from extensive databases, reducing response times and improving customer satisfaction. Input: irrelevant_question = "How did COVID-19 affect the financial crisis of 2008?" He has core competencies in data analytics, AI/ML and GenAI.

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Financial text generation using a domain-adapted fine-tuned large language model in Amazon SageMaker JumpStart

AWS Machine Learning Blog

JumpStart helps you quickly and easily get started with machine learning (ML) and provides a set of solutions for the most common use cases that can be trained and deployed readily with just a few steps. Defining hyperparameters involves setting the values for various parameters used during the training process of an ML model.

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Real-Real-World Programming with ChatGPT

O'Reilly Media

And if I switch tabs to view a paper from 2008, then a song from 2008 could start up. To provide some coherence to the music, I decided to use Taylor Swift songs since her discography covers the time span of most papers that I typically read: Her main albums were released in 2006, 2008, 2010, 2012, 2014, 2017, 2019, 2020, and 2022.

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Domain-adaptation Fine-tuning of Foundation Models in Amazon SageMaker JumpStart on Financial data

AWS Machine Learning Blog

JumpStart helps you quickly and easily get started with machine learning (ML) and provides a set of solutions for the most common use cases that can be trained and deployed readily with just a few steps. Defining hyperparameters involves setting the values for various parameters used during the training process of an ML model.

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