Nick Ball

Data Scientist

Nick has been a data scientist since the early 2000s. After obtaining an undergraduate degree in geology at Cambridge University in England (2000), he completed Masters (2001) and PhD (2004) degrees in Astronomy at the University of Sussex, then moved to North America, completing postdoctoral positions in Astronomy at the University of Illinois at Urbana-Champaign (2004-9, joint with the National Center for Supercomputing Applications), and the Herzberg Institute of Astrophysics in Victoria, BC, Canada (2009-2013). He joined Skytree, a startup company specializing in machine learning, in 2012,and in 2017 the Skytree technology and team was acquired by infosys. Machine learning has been part of his work since 2000, first applying it to large astronomical datasets, followed by wide ranges of application as a generalist data scientist at Skytree, Infosys, Oracle, and now Dotscience.

Tuesday, October 1
1:30 pm
1:55 pm
Robertson 2
Most AI/ML projects start shipping models into production, where they can deliver business value, using the no-process process. That is, people just do their best by creating an ad-hoc process with familiar tools. This works for tiny teams at first, but as the team grows you'll discover significant chaos and pain trying to operationalize AI.
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