Presented By O'Reilly and Cloudera
Make Data Work
September 25–26, 2017: Training
September 26–28, 2017: Tutorials & Conference
New York, NY
Michael Balint

Michael Balint
Senior Manager, Applied Solutions Engineering, NVIDIA

@michaelbalint

Michael Balint is a senior manager of applied solutions engineering at NVIDIA. Previously, Michael was a White House Presidential Innovation Fellow, where he brought his technical expertise to projects like Vice President Biden’s Cancer Moonshot program and Code.gov. Michael has had the good fortune of applying software engineering and data science to many interesting problems throughout his career, including tailoring genetic algorithms to optimize air traffic, harnessing NLP to summarize product reviews, and automating the detection of melanoma via machine learning. He is a graduate of Cornell and Johns Hopkins University.

Sessions

2:55pm3:35pm Wednesday, September 27, 2017
Data science & advanced analytics, Machine Learning & Data Science
Location: 1A 12/14 Level: Intermediate
Secondary topics:  Deep learning
Joshua Patterson (NVIDIA), Michael Balint (NVIDIA), Satish Varma Dandu (NVIDIA)
Average rating: ****.
(4.00, 1 rating)
How can deep learning be employed to create a system that monitors network traffic, operations data, and system logs to reliably flag risk and unearth potential threats? Satish Dandu, Joshua Patterson, and Michael Balint explain how to bootstrap a deep learning framework to detect risk and threats in operational production systems, using best-of-breed GPU-accelerated open source tools. Read more.