Broadcast Date: April 30, 2019
Amazon SageMaker offers a broad and deep set of capabilities that offer the choice and flexibility to build, train, and deploy machine learning models the way you are most comfortable with. With its modular capabilities, Amazon SageMaker offers you the modules for your mission critical workloads that you can pick and choose for best results. In this tech talk, we will provide an overview of these capabilities including Amazon Elastic Inference for fast inference at low cost, Amazon SageMaker Neo for training models once and running them anywhere, and Automatic Model Tuning for the best model accuracy.
- Explore Amazon Elastic Inference, Amazon SageMaker Neo, built-in algorithms, and automatic model tuning
- Understand the criteria for selecting the right capabilities for your use case
- Learn best practices to train and deploy models efficiently
Who Should Attend?
Developers, Data Scientists, Researchers
- Poorna Perumalla, Sr. Software Development Engineer, AWS
- Vin Sharma, Sr. Software Development Manager, AWS
To learn more about the services featured in this talk, please visit:
Service How To
December 19th, 2018 | 1:00 PM PT
Developing Deep Learning Models for Computer Vision with
Amazon EC2 P3 Instances.