Deeplearning4j Alternatives - Java Machine Learning

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Description

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.

Code Quality Rank: L1

Programming language: Java

Tags: Machine Learning

Latest version: v1.0.0

Deeplearning4j alternatives and similar libraries

Based on the "Machine Learning" category

Apache Spark

9.9 9.9 Deeplearning4j VS Apache Spark

Data analytics cluster computing framework.
Apache Flink

9.7 9.9 L2 Deeplearning4j VS Apache Flink

Fast and reliable large-scale data processing engine.
Apache Hadoop

9.7 9.9 L1 Deeplearning4j VS Apache Hadoop

Storage and large-scale processing of data-sets on clusters of commodity hardware.
Smile

8.7 7.2 L2 Deeplearning4j VS Smile

The Statistical Machine Intelligence and Learning Engine provides a set of machine learning algorithms and a visualization library.
Apache Mahout

8.1 8.0 L3 Deeplearning4j VS Apache Mahout

Scalable algorithms focused on collaborative filtering, clustering and classification.
DeepDive

7.5 0.0 Deeplearning4j VS DeepDive

Creates structured information from unstructured data and integrates it into an existing database.
Oryx 2

7.4 4.9 L4 Deeplearning4j VS Oryx 2

A framework for building real-time large scale machine learning applications, which also includes end-to-end applications for collaborative filtering, classification, regression, and clustering.
Porcupine

6.9 7.3 Deeplearning4j VS Porcupine

On-device wake word detection engine powered by deep learning.
DatumBox

6.6 4.3 L3 Deeplearning4j VS DatumBox

Provides several algorithms and pre-trained models for natural language processing.
H2O

6.5 9.6 Deeplearning4j VS H2O

Analytics engine for statistics over big data.
JSAT

5.5 6.1 L2 Deeplearning4j VS JSAT

Algorithms for pre-processing, classification, regression, and clustering with support for multi-threaded execution.
Weka

4.9 7.3 Deeplearning4j VS Weka

Collection of algorithms for data mining tasks ranging from pre-processing to visualization.

* Code Quality Rankings and insights are calculated and provided by Lumnify.
They vary from L1 to L5 with "L5" being the highest. Visit our partner's website for more details.

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README

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

Deeplearning4j

Distributed and multi-threaded deep learning library.