OVERVIEW This workshop is designed as a follow-up to the basic introduction to machine learning earlier in this series. We will cover several examples in Python and compare different implementations. […]
OVERVIEW This workshop will cover some more advanced topics in computing on the U-M Great Lakes Cluster. Topics to be covered include a review of common parallel programming models and […]
OVERVIEW This workshop will cover some more advanced topics in computing on the U-M Great Lakes Cluster. Topics to be covered include a review of common parallel programming models and […]
OVERVIEW For growing data volumes, how we manage data becomes more important. This session will cover the basics of managing data in a research environment such as those at ARC […]
OVERVIEW This workshop will cover some more advanced topics in computing on the U-M Great Lakes Cluster. Topics to be covered include a review of common parallel programming models and […]
OVERVIEW For growing data volumes, how we manage data becomes more important. This session will cover the basics of managing data in a research environment such as those at ARC […]
OVERVIEW This workshop will cover some more advanced topics in computing on the U-M Great Lakes Cluster. Topics to be covered include a review of common parallel programming models and […]
OVERVIEW This workshop will go over methods and best practices for running machine learning applications on Great Lakes. We will briefly outline machine learning before stepping through a hands-on example […]
OVERVIEW This workshop will provide a gentle introduction to using the multiprocessing package in Python for parallelizing and speeding up code. We will use hands-on programming exercises to demonstrate how […]
OVERVIEW This workshop will cover some more advanced topics in computing on the U-M Great Lakes Cluster. Topics to be covered include a review of common parallel programming models and […]