Machine Learning Pipelines - Joseph Bradley - Databricks
Spark and Spark Streaming at Netfix-(Kedar Sedekar and Monal Daxini, Netflix)
Digital Attribution Modeling Using Apache Spark-(Anny Chen and William Yan, Adobe)
Advanced Data Science with Apache Spark-(Reza Zadeh, Stanford)
Building a Location Based Social Graph in Spark at InMobi-(Seinjuti Chatterjee and Ian Anderson, InMobi)
Visual Api Training
Real Time Fuzzy Matching with Spark and Elastic Search-(Sonal Goyal, Nube)
Dev Ops Training
Cassandra and Spark: Optimizing for Data Locality-(Russell Spitzer, DataStax)
Spark in the Wild: An In-Depth Analysis of 50+ Production Deployments-(Arsalan Tavakoli Shiraji, Databricks)
IndexedRDD: Efficeint Fine-Grained Updates for RDD's-(Ankur Dave, UC Berkeley)
A Data Frame Abstraction Layer for SparkR-(Chris Freeman, Alteryx)
How to Boost 100x Performance for Real World Application with Apache Spark-(Grace Huang and Jiangang Duan, Intel)
Accelerating Innovation with Spark-(Beth Smith, IBM)
Large-Scale Lasso and Elastic-Net Regularized Generalized Linear Models (DB Tsai and Steve Hillion, Netflix and Alpine Data Labs)
Spark-on-Yarn: The Road Ahead-(Marcelo Vanzin, Cloudera)
Spark at NASA/JPL-(Chris Mattmann, NASA/JPL)
Making Sense of Spark Performance-(Kay Ousterhout, UC Berkeley)
Hadoop and Spark-Perfect Together-(Arun C. Murthy, Hortonworks)