AWS re:Invent 2022 - Train and host foundation models with PyTorch on AWS (AIM404)

Pre-training foundation models on Amazon SageMaker | Step 2: Train model | Amazon Web ServicesПодробнее

AWS re:Invent 2022 - [NEW] Easily build, train, and deploy ML models using geospatial data (AIM218)Подробнее

AWS re:Invent 2022 - Train ML models at scale with Amazon SageMaker, featuring AI21 Labs (AIM301)Подробнее

At-scale Training with pyTorch and Amazon SageMaker | Andrea OlgiatiПодробнее

AWS re:Invent 2022 - AI parallelism: How Amazon Search scales deep-learning training (CMP209)Подробнее

How to host and scale Pytorch Models on AWSПодробнее

AWS re:Invent 2023 - Large model training on AWS Deep Learning AMIs & PyTorch, ft. Pinterest -AIM326Подробнее

AWS re:Invent 2022 - Building a product review classifier with transfer learning (BOA304)Подробнее

AWS re:Invent 2021 - Train ML models at scale with Amazon SageMaker, featuring AuroraПодробнее

AWS re:Invent 2022 - Minimizing the production impact of ML model updates w/shadow testing (AIM343)Подробнее

AWS re:Invent 2020: Train billion-parameter models with model parallelism on Amazon SageMakerПодробнее

AWS re:Invent 2019: [REPEAT] Deep learning applications using PyTorch, featuring Autodesk (AIM412-R)Подробнее

AWS re:Invent 2019: Deep learning applications with PyTorch, featuring Freshworks (AIM412-R1)Подробнее

AWS re:Invent 2018: Deep Learning Applications Using PyTorch, Featuring Facebook (AIM402-R)Подробнее