Broadcast Date: August 18, 2022, 2022
Managing compute instances to view, run, or share a notebook is tedious. Amazon SageMaker Studio Notebooks are one-click Jupyter notebooks that can be spun up quickly. The underlying compute resources are fully elastic, so you can easily dial up or down the available resources and the changes take place automatically in the background without interrupting your work. You can also share notebooks with others in a few clicks. They will get the exact same notebook, saved in the same place. Join us to get started using SageMaker Studio Notebooks.
- See how to launch and use SageMaker Studio Notebooks
- Learn how to install open-source extensions
- Learn how to track and manage training and data processing jobs and test machine learning model performance
Who Should Attend?
Data Scientists, Machine Learning Developers, Developers, Data Engineers
- Kunal Jha, Senior Product Manager, AWS
- Sean Morgan, Senior Machine Learning Solutions Architect
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.