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Spark and Deep Learning Experts digging deep into the internals of Spark Core, Spark SQL, DataFrames, Spark Streaming, MLlib, Graph X, BlinkDB, TensorFlow, Caffe, Theano, OpenDeep, DeepLearning4J, etc.

Deeper than a blog post or typical meetup, we'll explore and discuss the best practices and idioms of the code base across many areas including Spark's JVM Bytecode Generation, CPU-cache-aware Data Structures and Algorithms, Approximations, Probabilistic Data Structures, Shuffle and I/O Optimizations, Streaming Micro-batch Scheduling, Performance Tuning, Configuration, Monitoring, Auto-Scaling, etc.

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