Presented By O’Reilly and Cloudera
Make Data Work
March 5–6, 2018: Training
March 6–8, 2018: 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 on many Apache 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

1:50pm2:30pm Wednesday, March 7, 2018
Sponsored
Location: LL20 B
Ted Dunning (MapR)
Average rating: ****.
(4.67, 3 ratings)
Getting value from data at large scale and on a variety of time scales is hard. True, it's not as hard as it used to be, but you still don’t win by default. Ted Dunning explains why it takes good design, the right technology, and a pragmatic approach to succeed. Read more.
5:10pm5:50pm Wednesday, March 7, 2018
Ted Dunning (MapR)
Average rating: *****
(5.00, 1 rating)
Ted Dunning offers an overview of the rendezvous architecture, developed to be the "continuous integration" system for machine learning models. It allows always-hot zero latency rollout and rollback of new models and supports extensive metrics and diagnostics so models can be compared as they process production data. It can even hot-swap the framework itself with no downtime. Read more.
1:50pm2:30pm Thursday, March 8, 2018
Location: Table A (Expo Hall)
Ted Dunning (MapR)
If you're interested in machine learning and the logistical aspects of supporting it in production, come talk to Ted. He'll also discuss: data platforms, streaming architecture, Kubernetes, containers, and rendezvous architecture. Read more.