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

Ted Dunning
Chief Application Architect, MapR

Website | @ted_dunning

Ted Dunning is chief application architect at MapR. He’s also a board member for the Apache Software Foundation, a PMC member and committer of the Apache Mahout, Apache Zookeeper, and Apache Drill projects, and a mentor for various incubator projects. Ted has years of experience with machine learning and other big data solutions across a range of sectors. He has contributed to clustering, classification, and matrix decomposition algorithms in Mahout and to the new Mahout Math library and designed the t-digest algorithm used in several open source projects and by a variety of companies. Previously, Ted was chief architect behind the MusicMatch (now Yahoo Music) and Veoh recommendation systems and built fraud-detection systems for ID Analytics (LifeLock). Ted has coauthored a number of books on big data topics, including several published by O’Reilly related to machine learning, and has 24 issued patents to date plus a dozen pending. He holds a PhD in computing science from the University of Sheffield. When he’s not doing data science, he plays guitar and mandolin. He also bought the beer at the first Hadoop user group meeting.

Sessions

9:30am9:40am Wednesday, March 15, 2017
Sponsored keynote
Location: Grand Ballroom
Ted Dunning (MapR)
Average rating: ***..
(3.26, 38 ratings)
The internet of things is turning the internet upside down, and the effects are causing all kinds of problems. We have to answer questions about how to have data where we want it and computation where we need it—and we have to coordinate and control all of this while maintaining visibility and security. Ted Dunning shares solutions for this problem from across multiple industries and businesses. Read more.
4:20pm5:00pm Wednesday, March 15, 2017
Data science & advanced analytics
Location: 230 C Level: Advanced
Secondary topics:  Hardcore Data Science
Ted Dunning (MapR)
Average rating: ****.
(4.50, 6 ratings)
Ted Dunning offers an overview of tensor computing—covering, in practical terms, the high-level principles behind tensor computing systems—and explains how it can be put to good use in a variety of settings beyond training deep neural networks (the most common use case). Read more.