| Topic | Explaining and Accelerating Machine Learning for Finance |
| Speaker | Dr. Mark Bennett Senior Data Scientist – AI Nvidia Corporation |
| When | January 20, 2021 – 6:00PM |
| Where | Zoom Online Presentation RSVP or call 312.861.1100 |
Mark Bennett is from the Chicago area and has been working in large datasets and real-time high performance computing for over three decades. Mark is currently senior data scientist at Nvidia Corporation where he focuses on acceleration for financial machine learning.
He has taught financial analytics at the University of Iowa and the University of Chicago. Mark holds a Ph.D. from UCLA, an M.S. from the University of Southern California, and a B.S. with Distinction from the University of Iowa, all in computer science.
Bennett has worked with Argonne National Laboratory, Unisys, AT&T, Northrop Grumman, XR Trading Securities, and Bank of America. Bennett is also the co-author of Financial Analytics with R published by Cambridge University Press.
Faster Learning with GPUs and RAPIDS
Don’t miss this exciting meeting on machine learning with GPU computing. You’ll learn how those of you who look at algorithms and see opportunities for massive parallelism can apply that skill to problem solving.
Financial modelers can now use advanced computer architectures known as GPUs and a Python-based framework known as RAPIDS to speed up problems using big data and machine learning.
Using the technological advancements in the current generation of GPUs, rather than taking minutes to run, these problems will be solved in seconds.
Join Us As We Accelerate Analytics
In this talk, Dr. Bennett will show a detailed analysis of several million loans where the contribution of each feature is discovered via their Shapley values.
About Nvidia Corporation
Nvidia Corporation’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world.