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Tag: Amazon SageMaker

Efficiently fine-tune the ESM-2 protein language model with Amazon SageMaker | Amazon Web Services

In this post, we demonstrate how to efficiently fine-tune a state-of-the-art protein language model (pLM) to predict protein subcellular localization using Amazon SageMaker. ...

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Build a robust text-to-SQL solution generating complex queries, self-correcting, and querying diverse data sources | Amazon Web Services

Structured Query Language (SQL) is a complex language that requires an understanding of databases and metadata. Today, generative AI can enable people without SQL...

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....

Streamline diarization using AI as an assistive technology: ZOO Digital’s story | Amazon Web Services

ZOO Digital provides end-to-end localization and media services to adapt original TV and movie content to different languages, regions, and cultures. It makes globalization...

Run ML inference on unplanned and spiky traffic using Amazon SageMaker multi-model endpoints | Amazon Web Services

Amazon SageMaker multi-model endpoints (MMEs) are a fully managed capability of SageMaker inference that allows you to deploy thousands of models on a single...

Code Llama 70B is now available in Amazon SageMaker JumpStart | Amazon Web Services

Today, we are excited to announce that Code Llama foundation models, developed by Meta, are available for customers through Amazon SageMaker JumpStart to deploy...

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...

Skeleton-based pose annotation labeling using Amazon SageMaker Ground Truth | Amazon Web Services

Pose estimation is a computer vision technique that detects a set of points on objects (such as people or vehicles) within images or videos....

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...

Amazon SageMaker Feature Store now supports cross-account sharing, discovery, and access | Amazon Web Services

Amazon SageMaker Feature Store is a fully managed, purpose-built repository to store, share, and manage features for machine learning (ML) models. Features are inputs...

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...

Automate mortgage document fraud detection using an ML model and business-defined rules with Amazon Fraud Detector: Part 3 | Amazon Web Services

In the first post of this three-part series, we presented a solution that demonstrates how you can automate detecting document tampering and fraud at...

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