Research Computing and Data Workshop Series: Machine Learning: Introduction to Amazon SageMaker for Building, Training, and Tuning Models Automatically

Wednesday, March 24, 2021 10 a.m. to 11:30 a.m.

New in 2021! We are pleased to bring to the UCF Research community a series of workshops on scientific computing and research data management. These workshops are being jointly presented by UCF LibrariesUCF Graduate and Research IT, and UCF Advanced Research Computing Center (ARCC) and will feature some guest speakers from the broader research community. This series also includes Software and Data Carpentries workshops (http://carpentries.org) which have been made possible through the sponsorship of Dr. Elizabeth Klonoff, Vice President for Research and Dean, College of Graduate Studies.

The workshops are targeted to faculty, post-docs and student researchers and will be especially useful for those who are new to computational science and interested in learning about the resources available to them at UCF and beyond. Topics span the areas of research data management, high-performance computing, and programming for scientific analysis and will feature some sessions with hands-on learning.

The March 24 session details are:

Title: Machine Learning: Introduction to Amazon SageMaker for Building, Training, and Tuning Models Automatically (hands-on)

Description:

Please note that at this time the workshops are only being offered to faculty, post-docs and students who are actively engaged in research as we have limited capacity due to the hands-on nature of the sessions.

This workshop will consist of a 45-minute presentation and 45-minute hands-on lab. In the presentation, we will introduce you to Amazon SageMaker, which helps data scientists and developers to prepare, build, train, and deploy high-quality machine learning (ML) models quickly by bringing together a broad set of capabilities purpose-built for machine learning. A key aspect of training machine learning models is the ability to tune them to the highest accuracy. In the lab, you will learn how to train and tune your ML models and deploy them into production. You will also learn real-time and and batch inference techniques to get predictions from ML models.

Presenters: 

Sherry Ding, Ph.D. - AI/ML Solutions Architect, AWS
Gabriel Brackman - Solutions Architect, AWS

Registration: https://ucf.zoom.us/meeting/register/tJYpcOupqTosGtDY0CgaqbAHyHk4pBQNXGNg

For the complete line-up of upcoming 2021 Research Computing and Data Workshops, please visit: https://rci.research.ucf.edu/workshops/2021/

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