Featured Presenters: Michele Chambers & Ian Stokes-Rees


The vast open data science landscape is full of choices but can be overwhelming to the uninitiated. However, organizations that can distil the landscape to the key players are making giant strides in leveraging the unending innovations—including AI—to drive new business value.

How can you navigate the landscape to identify the key and the emerging players? Can your enterprise harness open source without descending into anarchy? How can you embrace R, Python and their thousands of powerful analytic packages without the accompanying legal risks? How do you see through the legacy vendor FUD and make open source work?

We're here to help—Continuum Analytics Computational Scientist Ian Stokes-Rees will help you embark on your enterprise's journey to Open Data Science in this webinar.

You will learn how to:

  • Navigate the open data science landscape
  • Champion open data science projects for success
  • See a practical AI demonstration for enterprises
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Deliver New Business Value with Open Data Science



Michele Chambers is the EVP Anaconda Business Unit at Continuum Analytics. She's responsible for Engineering, Sales, Marketing, and Product Management for Anaconda. She is the author of Big Data Big Analytics, Modern Analytics Methodologies and Advanced Analytics Methodologies. Her next book is Breaking Data Science Open, published by O'Reilly.

Michele is a 20-year veteran in advanced analytics, having served as the COO/President at RapidMiner, VP/GM of Advanced Analytics at Netezza (IBM) and Chief Strategy & Products Officer at Revolution Analytics (Microsoft).

She holds a MBA from Duke University and a BS in Computer Engineering.

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Breaking Data Science Open: How Open Data Science is Eating the World

Open Data Science in the AI Era
Breaking Data Science Open

We know you're busy—everyone who signs up for the webinar will receive the slides and recording from the webinar.

Featured Presenters: Michele Chambers & Ian Stokes-Rees

Wednesday, March 8th, 2017
2PM Central | 3PM Eastern | 12PM Pacific


Ian is a Computational Scientist who has had the opportunity to work on some of the biggest "Big Data" problems over the past decade. He loves Python and promotes it at every opportunity. Ian's greatest interest is in enabling communication, collaboration and discovery through numbers, narratives and interactive visualizations made possible by high performance computing infrastructure.

Ian's love of computers started with an Apple ][ and Logo at the age of 8. Two engineering degrees at the University of Waterloo (Canada) were followed by several years in the industry, developing algorithms and infrastructure for large computational problems. After a Ph.D. at Oxford (UK) working on the computing team for one the CERN particle physics experiments, Ian spent several years at Harvard University working on computational techniques for protein structure determination. Ian has been part of the engineering team at Continuum for the past 4 years.

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