August 2019
Intermediate to advanced
608 pages
7h 46m
Japanese
Content preview from 詳説 Deep Learning ―実務者のためのアプローチ
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付録END4J APIの使用方法
ND4JはJava仮想マシン（JVM）用の科学演算ライブラリです。商用環境で高速に動作するように設計されています。以下に主な特徴を挙げます。
- 多目的のn次元配列オブジェクト
- グラフィックスプロセッシングユニット（GPU）を含むマルチプラットフォーム機能
- 線形代数と信号処理の関数
![[注記]](/api/v2/epubs/urn:orm:book:9784873118802/files/images/note.png) |
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ND4SはND4JのScala言語バージョンです。 |
Java、Scala、Clojureのプログラマーは、その使い方の隔たりのために、NumPyやMatlabのようなデータ分析におけるとても強力なツールから遠ざけられています。Breezeのようなライブラリは、ディープラーニングやその他のタスクに必要となる、n次元配列もテンソルもサポートしていません。ND4JとND4Sは、計算負荷が高いシミュレーションが求められる気候モデルのようなタスク用に国立研究所で使われています。
ND4Jは、Pythonコミュニティーの直観的な科学演算ツールを、オープンソース、分散かつGPU対応のライブラリとしてJVMに提供します。構造的にはSLF4Jに似ています。ND4Jは、商用環境でアルゴリズムや他のライブラリとのインタフェースをJavaやScalaエコシステムに移植するための簡単な方法をエンジニアに提供します。
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ND4Jのオンライン完全ユーザーガイド ND4Jはこの付録で挙げるものよりも多くの操作をサポートしています。ND4Jの完全なユーザーガイドとしてはhttp://nd4j.org/userguide ... |
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