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Guest Speaker: Reza Zadeh

Overview:
We discuss how to combine the scalability of Spark with machine learning and graph processing. This talk covers a subset of material covered in Stanford’s CME 323: Distributed Algorithms and Optimization. Lessons focus on building and using machine learning at scale via MLlib and GraphX.

Topics covered include:

• Building scalable Machine Learning algorithms on Spark, discussing design decisions inside MLlib and GraphX

• Understand how primitives like Matrix Factorization are implemented in a distributed framework from the designers of MLlib

CME 323: http://stanford.edu/~rezab/dao (http://stanford.edu/%7Erezab/dao)

Bio: http://stanford.edu/~rezab/bio.html (http://stanford.edu/%7Erezab/bio.html)

Toronto Hadoop User Group (THUG) and Toronto Apache Spark meetup group are both listing and organizing this event: https://www.meetup.com/TorontoHUG/events/224677876/

Please RSVP to at least one of the events and we will union the list of participants.

Note:

• Please be aware that there is no limit for RSVP but the number of sits are limited.

• Please inform us in advance if you require any assistance because of mobility issues.

• Parking: some across the street in the green p. Close access to St. Andrew TTC Station.

Sponsors:

http://photos1.meetupstatic.com/photos/event/4/9/5/b/600_441018779.jpeg

Gurulink (http://gurulink.ca/) is providing food and drink for the attendees.

http://photos2.meetupstatic.com/photos/event/4/9/8/c/600_441018828.jpeg

Paytm Labs (http://paytmlabs.com/) is generously offering their office space for this event.

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