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Deeplearning4j is an open source deep learning library written for Java and the Java Virtual Machine and a computing framework with wide support for deep learning algorithms. Deeplearning4j includes implementations of the restricted Boltzmann machine, deep belief net, deep autoencoder, stacked denoising autoencoder and recursive neural tensor network, as well as word2vec, doc2vec and GloVe. These algorithms all include distributed parallel versions that integrate with Hadoop and Spark. It is commercially supported by the startup Skymind. ==Introduction== Deeplearning4j relies on the widely used programming language, Java - though it is compatible with Clojure and includes a Scala API. It is powered by its own open-source numerical computing library, ND4J, and works with both CPUs and GPUs. Deeplearning4j is an open source project primarily developed by a machine learning group in San Francisco led by Adam Gibson. Deeplearning4j is the only open-source project listed on Google's Word2vec page for its Java implementation. Deeplearning4j has been used in a number of commercial and academic applications. The code is hosted on GitHub〔(Deeplearning4j source code )〕 and a support forum is maintained on Google Groups.〔(Deeplearning4j Google Group )〕 The framework is composable, meaning shallow neural nets such as restricted Boltzmann machines, convolutional nets, autoencoders and recurrent nets can be added to one another to create deep nets of varying types. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Deeplearning4j」の詳細全文を読む スポンサード リンク
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