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Introduction to Machine Learning on AWS

Aug 29 @ 1:00 pm - 2:30 pm

Introduction to Machine Learning on AWS

SPEAKER:

Kate Werling, AWS Solutions Architect

 

ABSTRACT:

At Amazon, we’ve been making huge investments in ML since 1995. Within AWS, we’ve been focused on bringing this knowledge and capability to our customers. In doing so, we have created the Machine Learning stack that allows everyone from extremely advanced Machine Learning practitioners to developers with little to no AI experience to integrate AI functionality into their applications. This presentation will walk through the various service offerings on AWS today such as the state-of-the art P3 instances, available on-demand any powered by Nvidia Tesla V100 GPU’s, Amazon SageMaker, our machine learning platform, and Rekognition, which is our managed computer-vision service.

 

WEB/CONFERENCE CALL INFO: We are going to use the NC State WebEx for the web conference.Please note that this WebEx belongs to NC State and can not be downloaded directly from Cisco. Also, it should work on iPhones and iPads via the WebExApp. A good internet connection is recommended. For better audio, please join via computer and then have the meeting call your number or call in directly using one of the numbers below. When not speaking, please mute your phone to avoid background noise. When it’s time, join the WebEx meeting from here:

https://wolfmeeting.ncsu.edu/orion/joinmeeting.do?MTID=b208fc6d7bbfe3e35daffa6a96c4515a

 

 

919-513-9329 (WolfMeeting)

Access Code: 996 474 981

 

Details

Date:
Aug 29
Time:
1:00 pm - 2:30 pm

Venue

Partners I, 1017 Main Campus Dr, Raleigh, NC 27606, USA
800 Main Campus Dr United States

Organizer

lascalendar@ncsu.edu
Email:
lascalendar@ncsu.edu

Connect With Us

LAS aims to bring together a multi-disciplinary group of academic, industry, and government researchers, analysts and managers together to re-engineer the intelligence analysis process to promote predictive analysis. LAS will do this by conducting both classified and unclassified research in a variety of areas of research. The research done in this area will serve as the foundation for mission effects and integrated back into the enterprise.

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