Deep Learning on the JVM
How to use the DL4J open source project for Spark and Hadoop deep learning on the JVM.
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DL4J is a pretty awesome open source project that works with Spark and Hadoop. Deep Learning 4J also works as a YARN app! It includes Text, NLP, Canova Vectorization Lib for ML, Scientific computing for the JVM, distributed with clusters, and works with CUDA GPU kernels.
Take a look at the Quick Start.
DL4J is used for anomaly detection (fraud detection), recommender systems, predictive analytics with logs and image recognition.
In a related open source project, Skymind built a numerical computing library ND4J, or n-dimensional arrays for Java, essentially porting Numpy to the JVM. ND4J powers Deeplearning4j, since deep-learning relies heavily on linear algebra and calculus. And the real work of ND4J is done in C++ with libnd4j. .
It is very easy to get started and run their code in IntelliJ, even on an average machine the results are quick.
Skymind and Hortonworks will be presenting an in-depth DL4j + Spark on HDP talk at the 2016 Hadoop Summit in San Jose, CA
Simple Setup to Run the Examples (Must Have JDK, Maven, and IntelliJ)
git clone https://github.com/deeplearning4j/dl4j-0.4-examples.git cd dl4j-0.4-examples/ mvn clean install brew install homebrew/science/deeplearning4j-cli
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