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Tag: MLops

Integrate HyperPod clusters with Active Directory for seamless multi-user login | Amazon Web Services

Amazon SageMaker HyperPod is purpose-built to accelerate foundation model (FM) training, removing the undifferentiated heavy lifting involved in managing and optimizing a large training...

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Nielsen Sports sees 75% cost reduction in video analysis with Amazon SageMaker multi-model endpoints | Amazon Web Services

This is a guest post co-written with Tamir Rubinsky and Aviad Aranias from Nielsen Sports. Nielsen Sports...

Build a contextual text and image search engine for product recommendations using Amazon Bedrock and Amazon OpenSearch Serverless | Amazon Web Services

The rise of contextual and semantic search has made ecommerce and retail businesses search straightforward for its consumers. Search engines and recommendation systems powered...

Enable single sign-on access of Amazon SageMaker Canvas using AWS IAM Identity Center: Part 2 | Amazon Web Services

Amazon SageMaker Canvas allows you to use machine learning (ML) to generate predictions without having to write any code. It does so by covering...

Optimize price-performance of LLM inference on NVIDIA GPUs using the Amazon SageMaker integration with NVIDIA NIM Microservices | Amazon Web Services

NVIDIA NIM microservices now integrate with Amazon SageMaker, allowing you to deploy industry-leading large language models (LLMs) and optimize model performance and cost. You...

Federated learning on AWS using FedML, Amazon EKS, and Amazon SageMaker | Amazon Web Services

This post is co-written with Chaoyang He, Al Nevarez and Salman Avestimehr from FedML. Many organizations are...

AI and Big Data Expo North America announces leading Speaker Lineup

SANTA CLARA, CA, Mar 7, 2024 - (ACN Newswire) - The AI and Big Expo North America, the leading event for Enterprise AI, Machine...

Automate Amazon SageMaker Pipelines DAG creation | Amazon Web Services

Creating scalable and efficient machine learning (ML) pipelines is crucial for streamlining the development, deployment, and management of ML models. In this post, we...

How Axfood enables accelerated machine learning throughout the organization using Amazon SageMaker | Amazon Web Services

This is a guest post written by Axfood AB.  In this post, we share how Axfood, a...

Techniques and approaches for monitoring large language models on AWS | Amazon Web Services

Large Language Models (LLMs) have revolutionized the field of natural language processing (NLP), improving tasks such as language translation, text summarization, and sentiment analysis....

Detect anomalies in manufacturing data using Amazon SageMaker Canvas | Amazon Web Services

With the use of cloud computing, big data and machine learning (ML) tools like Amazon Athena or Amazon SageMaker have become available and useable...

How BigBasket improved AI-enabled checkout at their physical stores using Amazon SageMaker | Amazon Web Services

This post is co-written with Santosh Waddi and Nanda Kishore Thatikonda from BigBasket. BigBasket is India’s largest...

How Booking.com modernized its ML experimentation framework with Amazon SageMaker | Amazon Web Services

This post is co-written with Kostia Kofman and Jenny Tokar from Booking.com. As a global leader in...

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