0.9.0
Deeplearning4J
    Workspaces feature added (faster training performance + less memory) Link
    SharedTrainingMaster added for Spark network training (improved performance) Link 1, Link 2
    ParallelInference added - wrapper that server inference requests using internal batching and queues Link
    ParallelWrapper now able to work with gradients sharing, in addition to existing parameters averaging mode Link
    VPTree performance significantly improved
    CacheMode network configuration option added - improved CNN and LSTM performance at the expense of additional memory use Link
    LSTM layer added, with CuDNN support Link (Note that the existing GravesLSTM implementation does not support CuDNN)
    New native model zoo with pretrained ImageNet, MNIST, and VGG-Face weights Link
    Convolution performance improvements, including activation caching
    Custom/user defined updaters are now supported Link
    Evaluation improvements
      EvaluationBinary, ROCBinary classes added: for evaluation of binary multi-class networks (sigmoid + xent output layers) Link
      Evaluation and others now have G-Measure and Matthews Correlation Coefficient support; also macro + micro-averaging support for Evaluation class metrics Link
      ComputationGraph and SparkComputationGraph evaluation convenience methods added (evaluateROC, etc)
      ROC and ROCMultiClass support exact calculation (previous: thresholded calculation was used) Link
      ROC classes now support area under precision-recall curve calculation; getting precision/recall/confusion matrix at specified thresholds (via PrecisionRecallCurve class) Link
      RegressionEvaluation, ROCBinary etc now support per-output masking (in addition to per-example/per-time-step masking)
      EvaluationCalibration added (residual plots, reliability diagrams, histogram of probabilities) Link 1 Link 2
      Evaluation and EvaluationBinary: now supports custom classification threshold or cost array Link
    Optimizations: updaters, bias calculation
    Network memory estimation functionality added. Memory requirements can be estimated from configuration without instantiating networks Link 1 Link 2
    New loss functions:
      Mixture density loss function Link
      F-Measure loss function Link
ND4J
    Workspaces feature added Link
    Native parallel sort was added
    New ops added: SELU/SELUDerivative, TAD-based comparisons, percentile/median, Reverse, Tan/TanDerivative, SinH, CosH, Entropy, ShannonEntropy, LogEntropy, AbsoluteMin/AbsoluteMax/AbsoluteSum, Atan2
    New distance functions added: CosineDistance, HammingDistance, JaccardDistance
DataVec
    MapFileRecordReader and MapFileSequenceRecordReader added Link 1 Link 2
    Spark: Utilities to save and load JavaRDD<List<Writable>> and JavaRDD<List<List<Writable>> data to Hadoop MapFile and SequenceFile formats Link
    TransformProcess and Transforms now support NDArrayWritables and NDArrayWritable columns
    Multiple new Transform classes
Arbiter
    Arbiter UI: Link
      UI now uses Play framework, integrates with DL4J UI (replaces Dropwizard backend). Dependency issues/clashing versions fixed.
      Supports DL4J StatsStorage and StatsStorageRouter mechanisms (FileStatsStorage, Remote UI via RemoveUIStatsStorageRouter)
      General UI improvements (additional information, formatting fixes)
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