Tag: DG
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Introducing the Amazon Comprehend flywheel for MLOps
The world we live in is rapidly changing, and so are the data and features that companies and customers use to train their models....
Extract non-PHI data from Amazon HealthLake, reduce complexity, and increase cost efficiency with Amazon Athena and Amazon SageMaker Canvas
In today’s highly competitive market, performing data analytics using machine learning (ML) models has become a necessity for organizations. It enables them to unlock...
Build a GNN-based real-time fraud detection solution using the Deep Graph Library without using external graph storage
Fraud detection is an important problem that has applications in financial services, social media, ecommerce, gaming, and other industries. This post presents an implementation...
Tune ML models for additional objectives like fairness with SageMaker Automatic Model Tuning
Model tuning is the experimental process of finding the optimal parameters and configurations for a machine learning (ML) model that result in the best...
Achieve high performance at scale for model serving using Amazon SageMaker multi-model endpoints with GPU
Amazon SageMaker multi-model endpoints (MMEs) provide a scalable and cost-effective way to deploy a large number of machine learning (ML) models. It gives you...
EU Metaverse Policy Should Consider Discrimination, Safety, Data Controls: Commission Official
“We want to make sure that the developments that we see in virtual worlds are fully in line with our European values from the...
Modular functions design for Advanced Driver Assistance Systems (ADAS) on AWS
Over the last 10 years, a number of players have developed autonomous vehicle (AV) systems using deep neural networks (DNNs). These systems have evolved...
Boomi uses BYOC on Amazon SageMaker Studio to scale custom Markov chain implementation
This post is co-written with Swagata Ashwani, Senior Data Scientist at Boomi. Boomi is an enterprise-level software as a service (SaaS) independent software vendor...
MLOps deployment best practices for real-time inference model serving endpoints with Amazon SageMaker
After you build, train, and evaluate your machine learning (ML) model to ensure it’s solving the intended business problem proposed, you want to deploy...
AWS and Hugging Face collaborate to make generative AI more accessible and cost efficient
We’re thrilled to announce an expanded collaboration between AWS and Hugging Face to accelerate the training, fine-tuning, and deployment of large language and vision...
Fine-tune text-to-image Stable Diffusion models with Amazon SageMaker JumpStart
In November 2022, we announced that AWS customers can generate images from text with Stable Diffusion models in Amazon SageMaker JumpStart. Stable Diffusion is...
New expanded data format support in Amazon Kendra
Enterprises across the globe are looking to utilize multiple data sources to implement a unified search experience for their employees and end customers. Considering...
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