Broadcast Date: May 27, 2022

Level: 200

State-of-the-art deep learning models can be difficult to train because of the cost, time, and skills required to optimize memory and compute. Join us for a discussion on how to overcome the common pitfalls of training deep learning models, and how Amazon SageMaker helps overcome these challenges by optimizing clusters of compute instances and more.

Learning Objectives

  • Discover how to accelerate training of large computer vision and NLP models
  • Learn how to get started quickly using Amazon SageMaker distributed training libraries and training compiler
  • Find out about tutorials and technical resources to get hands-on experience and dive deeper

Who Should Attend?

Data scientist, ML expert practitioners

Speakers

  • Mani Khanuja - Sr. AI/ML Specialist SA
  • Emily Webber - ML Specialist SA


Learn More

To learn more about the services featured in this talk, please visit:
https://aws.amazon.com/sagemaker/train

Intro body copy here about 2018 re:Invent launches.

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Compute

Service How To

December 19th, 2018 | 1:00 PM PT

Developing Deep Learning Models for Computer Vision with
Amazon EC2 P3 Instances.

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Containers

What's New / Cloud Innovation

December 11th, 2018 | 1:00 PM PT

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Data Lakes & Analytics

Webinar 1:

What's New / Cloud Innovation

December 10th, 2018 | 11:00 AM PT

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Webinar 2:

What's New / Cloud Innovation

December 12th, 2018 | 11:00 AM PT

EMBARGOED

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