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Scalable Machine Learning at Yahoo

September 28, 2015 @ 6:30 pm

Andy Feng, VP Architecture, Yahoo


*** Bring ID (e.g. Driver’s License) for eBay Security ***  
6:30 Doors Open, Food & Networking  
7:00 Presentation  
*** Please arrive by 7 PM due to Security ***

Event Details

At Yahoo, our Hadoop clusters manage almost all data about our users and contents. From these data on HDFS or event pipelines, machine learning (ML) techniques have been applied to discover mathematical models for search ranking, ad click prediction, and many more. 

Recently, Yahoo developed a distributed server for scalable ML on Hadoop grid with billions of training examples and input parameters. It provides several built-in ML operations such as MPI style AllReduce, and allows customized operations defined in Scala or Java. It supports MapReduce for parameter analysis and model conversion.

Yahoo implemented several massively scalable ML algorithms including Decision Trees, Logistic Regression, and Ad-Query Vectors.  These algorithms are now training ML models in minutes even for billions of parameters.  In this talk, we will provide a technical overview of Yahoo’s scalable ML solutions with use cases, and share our experience on leveraging strengths of Hadoop and Spark for machine learning.

Speaker Bio

Andy Feng is a VP Architecture at Yahoo leading the architecture and design of big data and machine learning initiatives. He is a PPMC member and commiter of the Apache Storm project and a contributor to the Apache Spark project. He served as a track chair and program committee member at Hadoop Summit and Spark Summit in both 2013 and 2014. At Yahoo, he has architected major platforms for personalization, ads serving, NoSQL, serving containers and messaging infrastructure.


Event page provided by ACM


September 28, 2015
6:30 pm
Event Category:


SF Bay ACM Chapter


eBay Whitman Campus, Community Building (Voices Conference Room)
2065 Hamilton Ave
San Jose, CA 95125 US
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