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Silicon Valley Machine Learning: May Meetup

May 31, 2017 @ 6:30 pm - 9:00 pm

LocationVISA Building M1 Auditorium


6:30 – 6:50 pm Networking & Food

6:50 – 7:00 pm Welcome & Announcements

7:00 – 8:30 pm Three 30-mins presentations

8:30 – 8:45 pm Q&A

9:00 pm Doors Close


Designing Distributed Machine Learning on Apache Spark by Joseph Bradley

Joseph Bradley is an Apache Spark Committer and PMC member working as a Machine Learning Software Engineer at Databricks. Previously, he was a postdoc at UC Berkeley after receiving his Ph.D. in Machine Learning from Carnegie Mellon.

How Basic Concepts of Distributed Engineering Helps Scale Data Science Algorithms Effectively Using Apache Spark and DataFrames by Nirmal Sharma

Nirmal Sharma is principle software engineer at WalmartLabs leading their big data team and is responsible for large-scale distributed systems, databases and algorithms. Prior to this, he worked as a data engineer at NETFLIX, where he was responsible for building scalable ML and data pipelines and tools using Hadoop and related technological stacks. He has 14 years of experience implementing, architecting and supporting large data platforms using distributed systems (Hadoop, Hive, Pig, Spark, and various other open source technologies), MPP systems, algorithms, and databases. He holds a B.Tech degree from IIT, Varanasi, India.

R4ML – new open-source R package for scalable machine learning from IBM by Alok Singh and Fred Reiss

Alok Singh is a Principal Engineer at the IBM Spark Technology Center, where he leads the R4ML project. He has built and architected multiple analytical frameworks and implemented various machine learning algorithms. His interest is in creating Big Data and scalable machine learning software and algorithms.

Fred Reiss is Chief Architect at the IBM Spark Technology Center in San Francisco and is one of the founding employees of the Center. Fred received his Ph.D. from UC Berkeley in 2006, then worked for IBM Research Almaden for the next nine years. At Almaden, Fred worked on the SystemML and SystemT projects, as well as on the research prototype of DB2 with BLU Acceleration. Fred has over 25 peer-reviewed publications and six patents.

Parking Information:

Enter on Metro Center drive, look for the signs for Visa M1 visitor parking, use the phone at the security gate to request access.

RSVP / Registration:

Provide a full name that matches a valid government ID to register. 

Valid government ID required to enter the premise.

Silicon Valley Machine Learning: May Meetup


May 31, 2017
6:30 pm - 9:00 pm
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Visa, Inc
900 Metro Center Blvd
Foster City, CA United States
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