Data Science in 30 Minutes: Accelerating Data Science Workflows on
GPUs with Bartley Richardson Join The Data Incubator and Bartley
Richardson, Senior Data Scientist and AI Infrastructure Manager at
NVIDIA or the next installment of our free online webinar series, Data
Science in 30 Minutes: Accelerating Data Science Workflows on GPUs.
Abstract: Data science, and data mining specifically, is the
exploration of vast amounts of data to discover actionable knowledge.
Today’s data scientists find answers to hard questions using trial
and error over multiple iterations, and they employ tools within the
Python ecosystem (e.g., Pandas, Numpy, and Scikit-learn) to enhance
their solutions and boost productivity. As larger amounts of data are
collected and need to be explored, the amount of time spent waiting
for results increases. The RAPIDS suite of open source software
libraries gives the data scientist the freedom to execute end-to-end
analytic pipelines on GPUs, enabling vastly accelerated processing and
training on large datasets. By using a familiar DataFrame API that
integrates with a variety of ML, DL, and graph algorithms,
transitioning from a traditional Python/Pandas environment to RAPIDS
is quick, and the speed gained by removing typical serialization costs
is large. In this talk, we’ll discuss RAPIDS and its goals, as well
as touch on some specific applications of RAPIDS that focus on
cybersecurity use cases. About the speakers: Bartley Richardson, PhD
is a Senior Data Scientist and Manager of AI Infrastructure at NVIDIA.
His primary focus is the research and application of GPU-accelerated
methods (including RAPIDS) that help solve today’s cybersecurity
challenges. Prior to NVIDIA, Bartley was a tech lead and performer on
multiple DARPA research projects, where he applied data science and
machine learning algorithms at-scale to large cyber and information
security problems. He was also the principal investigator of an IoT
research project which focused on using ML and DL techniques on large
amounts of IoT data to provide intelligence value. Michael Li is
President of Data Science at Pragmatic Institute, responsible for
defining and leading Pragmatic's data courses. Michael founded The
Data Incubator in 2014 as a platform for training and placing data
scientists. Previously, he worked as a data scientist (Foursquare),
Wall Street quant (D.E. Shaw, J.P. Morgan), and a rocket scientist
(NASA). He completed his PhD at Princeton as a Hertz fellow and read
Part III Maths at Cambridge as a Marshall Scholar. At Foursquare,
Michael discovered that his favorite part of the job was teaching and
mentoring smart people about data science and so he built up a
successful startup focused on what he really loves.
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22/08/2019 Last update