Deeplearning4j

DL4J takes advantage of the latest distributed computing frameworks including Apache Spark and Hadoop to accelerate training. On multi-GPUs, it is equal to Caffe in performance. The libraries are completely open-source, Apache 2.0, and maintained by the developer community and Skymind team. JVM/Python/C++. Deeplearning4j is written in Java and is compatible with any JVM language, such as Scala, Clojure or Kotlin. The underlying computations are written in C, C++ and Cuda. Keras will serve as the Python API.


References in zbMATH (referenced in 1 article )

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  1. Aggarwal, Charu C.: Neural networks and deep learning. A textbook (2018)