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 )

Showing result 1 of 1.
Sorted by year (citations)

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