Tutorial

The Guide to Stable Diffusion XL 1.0 Foundation Model in Amazon Bedrock

Introduction¶ Welcome to the comprehensive guide to the Stable Diffusion XL 1.0 (SDXL 1.0) foundation model from Stability AI. This powerful image model is now generally available in Amazon Bedrock, providing users with the ability to create complex, detailed, and visually stunning images with just a few words. In this guide, we will explore the …

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SageMaker: The Ultimate Guide to Model Deployment

Introduction¶ With the rapid advancement of machine learning (ML) and artificial intelligence (AI) technologies, model deployment has become a critical step in leveraging the power of ML models. However, deploying ML models has traditionally been a complex and time-consuming process. Fortunately, Amazon SageMaker has introduced new tools and improvements that revolutionize the way models are …

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Amazon SageMaker Clarify: Guide to Foundation Model Evaluations

Introduction¶ Amazon SageMaker Clarify is a powerful tool that enables customers to evaluate and interpret the performance of their machine learning (ML) models. With the latest update, SageMaker Clarify now supports Foundation Model (FM) evaluations, enhancing the model selection and customization workflow. In this comprehensive guide, we will explore how to leverage FM evaluations, using …

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AWS Partner CRM Connector: A Complete Guide for Seamless AWS Marketplace Integration

Guide Version: 1.0.0 Table of Contents¶ Introduction Key Features of AWS Partner CRM Connector Benefits of Utilizing AWS Partner CRM Connector How to Set Up AWS Partner CRM Connector How to Enable AWS Marketplace and ACE Pipeline Manager Features Utilizing Dashboard Feature to View AWS Marketplace Private Offers Summary Streamlining Field Sales Operations in Salesforce …

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Guide to Smart Sifting of Data for Amazon SageMaker Model Training

Introduction¶ Data plays a crucial role in the training of machine learning models. However, not all data is equally important for model training. Amazon SageMaker, a fully managed machine learning service, is introducing a new feature called “Smart Sifting.” Smart sifting allows you to utilize your live model during training to analyze incoming data samples …

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The Importance of Responsible AI

Artificial Intelligence (AI) has the potential to revolutionize industries and transform the way we live and work. However, with great power comes great responsibility. As AI becomes increasingly integrated into our daily lives, it is crucial that we ensure its ethical and responsible use. To address these concerns, Amazon Web Services (AWS) is proud to …

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Amazon SageMaker: Reducing Costs and Latency with New Inference Capabilities

With the ever-growing advancements in Machine Learning (ML), deploying ML models has become an essential part of many businesses. Amazon SageMaker has emerged as a popular platform for deploying and managing ML models easily. In its continuous pursuit of improving user experience and optimizing performance, Amazon SageMaker has recently introduced new inference capabilities. These capabilities …

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AWS announces OR1 for Amazon OpenSearch Service

Introduction¶ In a recent announcement, AWS introduced OR1 for the Amazon OpenSearch Service. This new feature brings a rearchitected storage system to managed clusters on OpenSearch. By leveraging Amazon S3 and other cloud technologies, OR1 offers increased durability and improved price-performance ratios. In this guide, we will explore the technical details of OR1 and how …

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Announcing Amazon SageMaker HyperPod

Introduction¶ Training machine learning models, especially for complex tasks such as financial modeling (FM), can be time-consuming and resource-intensive. Many organizations rely on graphics processing units (GPU) or Trainium-based instances to train their own FMs. While these instances offer cost-efficiency, the increasing complexity of training models, including the larger volumes of data and size of …

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