Presented By O'Reilly and Cloudera
Make Data Work
March 13–14, 2017: Training
March 14–16, 2017: Tutorials & Conference
San Jose, CA
Frederick Reiss

Frederick Reiss
Chief Architect, IBM


Fred Reiss is chief architect and one of the founding employees of the IBM Spark Technology Center in San Francisco. Previously, Fred worked for IBM Research Almaden for nine years, where he worked on the SystemML and SystemT projects as well as on the research prototype of DB2 with BLU Acceleration. He has over 25 peer-reviewed publications and six patents. Fred holds a PhD from UC Berkeley.


1:50pm2:30pm Wednesday, March 15, 2017
Data science & advanced analytics
Location: 210 C/G Level: Advanced
Secondary topics:  Deep learning, Healthcare
Michael Dusenberry (IBM Spark Technology Center), Frederick Reiss (IBM)
Average rating: *****
(5.00, 2 ratings)
Estimating the growth rate of tumors is a very important but very expensive and time-consuming part of diagnosing and treating breast cancer. Michael Dusenberry and Frederick Reiss describe how to use deep learning with Apache Spark and Apache SystemML to automate this critical image classification task. Read more.
4:20pm5:00pm Thursday, March 16, 2017
Data science & advanced analytics
Location: 230 C Level: Advanced
Secondary topics:  Hardcore Data Science
Frederick Reiss (IBM), Arvind S (IBM)
Many iterative machine-learning algorithms can only operate efficiently when a large matrix of training data fits in the main memory. Frederick Reiss and Arvind Surve offer an overview of compressed linear algebra, a technique for compressing training data and performing key operations in the compressed domain that lets you build models over big data with small machines. Read more.