Confirm and Proceed
View More
View Less
System Message
An unknown error has occurred and your request could not be completed. Please contact support.
Reserved - Scan in at least 10 minutes before the beginning of the session.
This has been added to your Planner. Please note: This is not a reserved seat.
Waitlisted - You may be assigned a reserved seat if one becomes available.

Please be sure to check the session schedule for any repeats of this session. In order to search for repeats of this session, please type the Session ID into the search bar at the top of the page.
Personal Calendar
Conference Event
There aren't any available sessions at this time.
Conflict Found
This session is already scheduled at another time. Would you like to...
Please enter a maximum of {0} characters.
{0} remaining of {1} character maximum.
Please enter a maximum of {0} words.
{0} remaining of {1} word maximum.
must be 50 characters or less.
must be 40 characters or less.
Session Summary
We were unable to load the map image.
This has not yet been assigned to a map.
Search Catalog
Replies ()
New Post
Microblog Thread
Post Reply
Your session timed out.
Meeting Summary

AIM410-R1 - [REPEAT 1] Build, Train, and Deploy ML Models with Amazon SageMaker

Session Description

Come and help build the most accurate text classification model possible. A fully managed machine learning (ML) platform, Amazon SageMaker enables developers and data scientists to build, train, and deploy ML models using built-in or custom algorithms. In this workshop, you learn how to leverage Keras/TensorFlow deep learning frameworks to build a text classification solution using custom algorithms on Amazon SageMaker. You package custom training code in a Docker container, test it locally, and then use Amazon SageMaker to train a deep learning model. You then try to iteratively improve the model to achieve a higher level of accuracy. Finally, you deploy the model in production so different applications within the company can start leveraging this ML classification service. Please note that to actively participate in this workshop, you need an active AWS account with admin-level IAM permissions to Amazon SageMaker, Amazon Elastic Container Registry (Amazon ECR), and Amazon S3.

Session Speakers
Additional Information
Artificial Intelligence & Machine Learning
400 - Expert
Please note that session information is subject to change.
Session Schedule