MLADS 2019 Spring
NVIDIA RAPIDS: Open-Source GPU Data Science on Azure
Traditional machine-learning workloads have yet to be GPU-accelerated the way deep learning and other neural net methods have. RAPIDS aims to change that, while maintaining the ease of use of the PyData ecosystem. The goal is to build a ridiculously fast open-source data science platform that allows practitioners to explore data, train ML algorithms and build applications while primarily staying in GPU memory.
During this lab we will provide a hands-on introduction to RAPIDS. It will begin with a brief introduction to RAPIDS and Azure ML (10-15 minutes). The remainder of the time will be a hands-on session on how to use RAPIDS to process and train a ML model.
Presenters
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Tom Drabas is a Senior Data Scientist at Microsoft. He has over 15 years of international experience working in airline, telecommunication and technology industries. He holds PhD in airline operations research field from the University of New South Wales. During his time at Microsoft he has published multiple books and authored a video series on data science, machine learning and distributed computing in Spark. His research interests include parallel, deep learning and machine learning algorithms and their applications.
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Keith Kraus is a manager in the AI infrastructure team at NVIDIA. He is a core developer of RAPIDS and works extensively on the Python interface, API design, distributed computation architecture, and big data integration. Prior to joining NVIDIA, Keith worked in cybersecurity, focused on building a GPU-Accelerated big data solution for advanced threat detection. Keith holds an MEng in networked information systems from Stevens Institute of Technology.
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Paul Mahler is a Senior Data Scientist at NVIDIA in Boulder, CO. At NVIDIA, Paul’s focus has been on building tools that accelerate data science workflows by leveraging the power of GPU technology. Prior to NVIDIA, Paul worked as a data scientist at a Fin Tech start-up in San Francisco, and as an associate manager in Accenture Tech Labs. In a different life, Paul was an economist who worked at the World Bank and Fannie Mae.
Greater team
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Joshua Patterson, General Manager of AI Infrastructure, NVIDIA Josh leads engineering for RAPIDS.AI, and is a former White House Presidential Innovation Fellow. Prior to NVIDIA, Josh worked with leading experts across public sector, private sector, and academia to build a next-generation cyber defense platform. His current passions are graph analytics, machine learning, and large-scale system design. Josh also loves storytelling with data and creating interactive data visualizations. Josh holds a B.A. in economics from the University of North Carolina at Chapel Hill and an M.A. in economics from the University of South Carolina Moore School of Business.
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Bartley Richardson
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Brad Rees
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Michael Beaumont