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Tag: Scheduler

Accelerate client success management through email classification with Hugging Face on Amazon SageMaker | Amazon Web Services

This is a guest post from Scalable Capital, a leading FinTech in Europe that offers digital wealth management and a brokerage platform with a...

Enable pod-based GPU metrics in Amazon CloudWatch | Amazon Web Services

In February 2022, Amazon Web Services added support for NVIDIA GPU metrics in Amazon CloudWatch, making it possible to push metrics from the Amazon...

Weaponized Windows Installers Target Graphic Designers in Crypto Heist

Attackers are targeting 3D modelers and graphic designers with malicious versions of a legitimate Windows installer tool in a cryptocurrency-mining campaign that's been ongoing...

New feature: schedule your tournament matches in bulk – Toornament Blog

The way you schedule your tournament matches has been greatly improved. You can now set the date and time of your matches in bulk...

Deploy thousands of model ensembles with Amazon SageMaker multi-model endpoints on GPU to minimize your hosting costs | Amazon Web Services

Artificial intelligence (AI) adoption is accelerating across industries and use cases. Recent scientific breakthroughs in deep learning (DL), large language models (LLMs), and generative...

Exploring summarization options for Healthcare with Amazon SageMaker | Amazon Web Services

In today’s rapidly evolving healthcare landscape, doctors are faced with vast amounts of clinical data from various sources, such as caregiver notes, electronic health...

Host ML models on Amazon SageMaker using Triton: ONNX Models | Amazon Web Services

ONNX (Open Neural Network Exchange) is an open-source standard for representing deep learning models widely supported by many providers. ONNX provides tools for optimizing...

Host ML models on Amazon SageMaker using Triton: CV model with PyTorch backend | Amazon Web Services

PyTorch is a machine learning (ML) framework based on the Torch library, used for applications such as computer vision and natural language processing. One...

Create high-quality images with Stable Diffusion models and deploy them cost-efficiently with Amazon SageMaker | Amazon Web Services

Text-to-image generation is a task in which a machine learning (ML) model generates an image from a textual description. The goal is to generate...

Get insights on your user’s search behavior from Amazon Kendra using an ML-powered serverless stack | Amazon Web Services

Amazon Kendra is a highly accurate and intelligent search service that enables users to search unstructured and structured data using natural language processing (NLP)...

Schedule your notebooks from any JupyterLab environment using the Amazon SageMaker JupyterLab extension | Amazon Web Services

Jupyter notebooks are highly favored by data scientists for their ability to interactively process data, build ML models, and test these models by making...

Host ML models on Amazon SageMaker using Triton: Python backend | Amazon Web Services

Amazon SageMaker provides a number of options for users who are looking for a solution to host their machine learning (ML) models. Of these...

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