Release Notes

Initial multi-GPU support viable for standalone and Spark. Refactored the Spark API significantly Added CuDNN wrapper Performance improvements for ND4J Introducing DataVec: Lots of new functionality for transforming, preprocessing, cleaning data. (This replaces Canova) New DataSetIterators for feeding neural nets with existing data: ExistingDataSetIterator, Floats(Double)DataSetIterator, IteratorDataSetIterator New learning algorithms for word2vec and paravec: CBOW and PV-DM respectively New native ops for better performance: DropOut, DropOutInverted, CompareAndSet, ReplaceNaNs Shadow asynchronous datasets prefetch enabled by default for both MultiLayerNetwork and ComputationGraph Better memory handling with JVM GC and CUDA backend, resulting in significantly lower memory footprint Get Started With Deeplearning4j Resources Roadmap for Summer 2016 Deep Q Learning, integration with Open AI’s Gym Deeplearning4s Scala API Standard NN configuration file shared with Keras

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