November 2017
Intermediate to advanced
328 pages
6h 51m
Japanese
Content preview from 入門 PySpark ―PythonとJupyterで活用するSpark 2エコシステム
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176
8
章
TensorFrames
8.5
まとめ
本章では、特徴エンジニアリングの構成要素を含む、ニューラルネットワークとディープラーニングの
基礎を見ました。ディープラーニングが新たな盛り上がりを見せていることを踏まえて TensorFlowを紹
介し、TensorFramesを通じてTensorFlow がApache Sparkと密接に連携できることを示しました。
TensorFramesはディープラーニングの強力なツールであり、データサイエンティストやデータエン
ジニアは TensorFlow を使ってSpark のDataFrameに格納されたデータを処理できるようになります。
TensorFramesはApache Sparkの可能性を、ニューラルネットワークの学習プロセスに基づく強力な
ディープラーニングのツールセットにまで押し広げてくれます。ディープラーニングについて学び続け
るには、次のリソースが大きな助けになることでしょう。
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TensorFlow（https://www.tensorflow.org/）
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TensorFlow | Get Started（https://www.tensorflow.org/get_started/）
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TensorFlow | Guides（https://www.tensorflow.org/tutorials/）
●
Deep Learning on Databricks（https://databricks.com/blog/20 ...
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