
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.
Data Lakes & Analytics
Webinar 1:
What's New / Cloud Innovation
December 10th, 2018 | 11:00 AM PT
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