Deeplearning4J Deep Learning Framework

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A Deeplearning4J Deep Learning Framework is a deep network learning system maintained by the DL4J project.



References

2017b

  • https://deeplearning4j.org/overview
    • QUOTE: DeepLearning4J is a java based toolkit for building, training and deploying Neural Networks.

      DeepLearning4J has the following sub-projects.

      • DataVec performs data ingestion, normalization and transformation into feature vectors
      • DeepLearning4j provides tools to configure neural networks and build computation graphs
      • DL4J-Examples contains working examples for classification and clustering of images, time series and text.
      • Keras Model Import helps import trained models from Python and Keras to DeepLearning4J and Java.
      • ND4J allows Java to access Native Libraries to quickly process Matrix Data on CPUs or GPUs.
      • ScalNet is a Scala wrapper for Deeplearning4j inspired by Keras. Runs on multi-GPUs with Spark.
      • RL4J implements Deep Q Learning, A3C and other reinforcement learning algorithms for the JVM.
      • Arbiter helps search the hyperparameter space to find the best neural net configuration.

2017b

2014