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Build and deploy a UI for your generative AI applications with AWS and Python

AWS Machine Learning - AI

Prerequisites As a prerequisite, you need to enable model access in Amazon Bedrock and have access to a Linux or macOS development environment. You can download Python from the official website or use your Linux distribution’s package manager. Access to Amazon Bedrock foundation models is not granted by default. The AWS CDK.

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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 - AI

That’s where the new Amazon EMR Serverless application integration in Amazon SageMaker Studio can help. In this post, we demonstrate how to leverage the new EMR Serverless integration with SageMaker Studio to streamline your data processing and machine learning workflows.

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

AWS Machine Learning - AI

Prerequisites To implement the solution outlined in this post, you must have the following: A Linux or MacOS development environment with at least 20 GB of free disk space. Performance optimization The serverless architecture used in this post provides a scalable solution out of the box. It can be a local machine or a cloud instance.

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Weekly Update 6-3-2019

Linux Academy

This week, we’re talking all about serverless computing, what it is, why it’s relevant, and the release of a free course that can be enjoyed by everyone on the Linux Academy platform, including Community Edition account members. Serverless Computing: What is it? Configure auto-scaling with load balancers.

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Build RAG-based generative AI applications in AWS using Amazon FSx for NetApp ONTAP with Amazon Bedrock

AWS Machine Learning - AI

Our solution uses an FSx for ONTAP file system as the source of unstructured data and continuously populates an Amazon OpenSearch Serverless vector database with the user’s existing files and folders and associated metadata. The chatbot application container is built using Streamli t and fronted by an AWS Application Load Balancer (ALB).

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Weekly Update 5-20-2019

Linux Academy

Great news for all of our Linux Academy students; Red Hat Enterprise is already available to try out in Linux Academy’s Cloud Playground! We have more information on t he release in general and all the new features in our podcast Linux Action News and episode 105. Configuring SELinux. Creating Confined Users in SELinux.

Linux 60
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Advanced RAG patterns on Amazon SageMaker

AWS Machine Learning - AI

It started as a feature-poor service, offering only one instance size, in one data center, in one region of the world, with Linux operating system instances only. There was no monitoring, load balancing, auto-scaling, or persistent storage at the time.