Deeplearning4J is an Apache 2.0-licensed, open-source, distributed neural net library written in Java and Scala.
Deeplearning4J integrates with Hadoop and Spark and runs on several backends that enable use of CPUs and GPUs. The aim is to create a plug-and-play solution that is more convention than configuration, and which allows for fast prototyping.
The most recent stable release in Maven Central is 0.4-rc3.8, and the current master is 0.4-rc3.9-SNAPSHOT. For more on working with snapshots, see this page.
Deeplearning4j alternatives and similar libraries
Based on the "Machine Learning" category
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Monorepo of Deeplearning4j
Welcome to the new monorepo of Deeplearning4j that contains the source code for all the following projects, in addition to the original repository of Deeplearning4j moved to [deeplearning4j](deeplearning4j):
To build everything, we can use commands like
./change-cuda-versions.sh x.x ./change-scala-versions.sh 2.xx ./change-spark-versions.sh x mvn clean install -Dmaven.test.skip -Dlibnd4j.cuda=x.x -Dlibnd4j.compute=xx
mvn -B -V -U clean install -pl '!jumpy,!pydatavec,!pydl4j' -Dlibnd4j.platform=linux-x86_64 -Dlibnd4j.chip=cuda -Dlibnd4j.cuda=9.2 -Dlibnd4j.compute=<your GPU CC> -Djavacpp.platform=linux-x86_64 -Dmaven.test.skip=true
An example of GPU "CC" or compute capability is 61 for Titan X Pascal.
Want some examples?
We have separate repository with various examples available: https://github.com/eclipse/deeplearning4j-examples
In the examples repo, you'll also find a tutorial series in Zeppelin: https://github.com/eclipse/deeplearning4j-examples/tree/master/tutorials