Mahout 1.0: Looking at the Future

Exciting news for Mahout: a move to support memory-based computational frameworks. Learn about Mahout 0.9 and what is being developed for 1.0

1st speaker:

Dmitriy Lyubimov (Mahout Committer and AgilOne Data Scientist)

There's lots of excitement around Spark, and Dmitriy is leading some new work on the Mahout project connected to Spark and Scala. Dmitriy will give a short presentation on the goals of this work and what it will mean for Mahout.

Bio:

Dmitriy holds a Data Scientist position with AgilOne. He has been through a number of start-ups focusing mostly on engineering aspects of Big Data Machine Learning and Analytics with occasional forays into big scale distributed Machine Learning Implementations and Applied Research. Dmitry is an Apache Mahout committer and a contributor to Apache Spark.

2nd speaker: Ted Dunning (Mahout Committer and MapR Chief Applications Architect)

Ted will describe the changes in Mahout, present some technical examples including some recent work in Anomaly Detection and a hint of deep learning and then open a discussion about future development in Mahout, especially the new support for in-memory computational frameworks as back-end.

Bio:

Ted is Chief Applications Architect at MapR Technologies and committer and PMC member of the Apache Mahout, Apache ZooKeeper, and Apache Drill projects and mentor for Apache Storm and Apache Spark. Most recently he helped expand the new version of Mahout Math library. Ted has built recommendation systems for music (MusicMatch, now Yahoo Music) and video (Veoh) and fraud detection systems for ID Analytics (now LifeLock). He has 24 issued patents to date. Ted has a PhD in computing science from University of Sheffield. When he’s not doing data science, he plays guitar and mandolin.

Attendance:

Please RSVP if you plan to attend. I do not yet know if there will be a way to attend remotely. If you can attend only remotely, please note that when you sign up. Thanks!