XSEDE HPC Workshop: Big Data and Machine Learning

Date: 
Tuesday, October 5, 2021 - 11:00am to Wednesday, October 6, 2021 - 5:30pm
Location: 

Due to the COVID-19 pandemic, this session will be available via zoom direct to desktops only.

XSEDE HPC Workshop: BIG DATA and Machine Learning

October 5-6, 2021

 

XSEDE, along with the Pittsburgh Supercomputing Center, is pleased to present a two day Big Data and Machine Learning workshop. This workshop will focus on topics such as Hadoop and Spark and will be presented using the Wide Area Classroom (WAC) training platform.

Due to COVID-19, this workshop will be remote, using Zoom.

 

Registration

Register by going to: https://portal.xsede.org/course-calendar

If you do not currently have an XSEDE Portal account, you will need to create one:

https://portal.xsede.org/my-xsede?p_p_id=58&p_p_lifecycle=0&p_p_state=maximized&p_p_mode=view&_58_struts_action=%2Flogin%2Fcreate_account

Should you have any problems with that process, please contact help@xsede.org and they will provide assistance.

 

Tentative Agenda

Tuesday, October 5
All times given are Eastern
11:00 Welcome
11:25 A Brief History of  Big Data
12:20 Intro to Spark
1:00 Lunch break
2:00 More Spark and Exercises
3:00 Intro to Machine Learning
5:00 Adjourn

 

Wednesday, October 6
All times given are Eastern
11:00 Machine Learning: Recommender System with Spark
1:00 Lunch break
2:00 Deep Learning with Tensorflow
5:00 Tying it All Together
5:30 Adjourn

 

Questions

Please address any questions to Tom Maiden at tmaiden@psc.edu.

 

XSEDE, the Extreme Science and Engineering Discovery Environment, is the most advanced, powerful, and robust collection of integrated digital resources and services in the world. It is a single virtual system that scientists and researchers can use to interactively share computing resources, data, and expertise. XSEDE integrates the resources and services, makes them easier to use, and helps more people use them.

 

https://www.psc.edu/resources/training/hpc-workshop-series/xsede-hpc-wor...