Apache Spark Deep Learning Cookbook: Over 80 recipes that streamline deep learning in a distributed environment with Apache Spark

Ahmed Sherif, Amrith Ravindra

  • 出版商: Packt Publishing
  • 出版日期: 2018-07-12
  • 售價: $2,110
  • 貴賓價: 9.5$2,005
  • 語言: 英文
  • 頁數: 474
  • 裝訂: Paperback
  • ISBN: 1788474228
  • ISBN-13: 9781788474221
  • 相關分類: SparkDeepLearning
  • 相關翻譯: Spark深度學習指南 (簡中版)
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商品描述

A solution-based guide to put your deep learning models into production with the power of Apache Spark

Key Features

  • Discover practical recipes for distributed deep learning with Apache Spark
  • Learn to use libraries such as Keras and TensorFlow
  • Solve problems in order to train your deep learning models on Apache Spark

Book Description

With deep learning gaining rapid mainstream adoption in modern-day industries, organizations are looking for ways to unite popular big data tools with highly efficient deep learning libraries. As a result, this will help deep learning models train with higher efficiency and speed.

With the help of the Apache Spark Deep Learning Cookbook, you'll work through specific recipes to generate outcomes for deep learning algorithms, without getting bogged down in theory. From setting up Apache Spark for deep learning to implementing types of neural net, this book tackles both common and not so common problems to perform deep learning on a distributed environment. In addition to this, you'll get access to deep learning code within Spark that can be reused to answer similar problems or tweaked to answer slightly different problems. You will also learn how to stream and cluster your data with Spark. Once you have got to grips with the basics, you'll explore how to implement and deploy deep learning models, such as Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN) in Spark, using popular libraries such as TensorFlow and Keras.

By the end of the book, you'll have the expertise to train and deploy efficient deep learning models on Apache Spark.

What you will learn

  • Set up a fully functional Spark environment
  • Understand practical machine learning and deep learning concepts
  • Apply built-in machine learning libraries within Spark
  • Explore libraries that are compatible with TensorFlow and Keras
  • Explore NLP models such as Word2vec and TF-IDF on Spark
  • Organize dataframes for deep learning evaluation
  • Apply testing and training modeling to ensure accuracy
  • Access readily available code that may be reusable

Who this book is for

If you're looking for a practical and highly useful resource for implementing efficiently distributed deep learning models with Apache Spark, then the Apache Spark Deep Learning Cookbook is for you. Knowledge of the core machine learning concepts and a basic understanding of the Apache Spark framework is required to get the best out of this book. Additionally, some programming knowledge in Python is a plus.

商品描述(中文翻譯)

《Apache Spark深度學習食譜》是一本以解決問題為導向的指南,教你如何將深度學習模型應用於Apache Spark的生產環境中。

重點特色:
- 探索使用Apache Spark進行分散式深度學習的實用方法
- 學習使用Keras和TensorFlow等庫
- 解決問題,以在Apache Spark上訓練深度學習模型

書籍描述:
隨著深度學習在現代工業中迅速普及,組織正在尋找將流行的大數據工具與高效的深度學習庫結合的方法。因此,這將有助於深度學習模型以更高的效率和速度進行訓練。

通過《Apache Spark深度學習食譜》的幫助,你將通過具體的實例來生成深度學習算法的結果,而不會陷入理論中。從設置Apache Spark進行深度學習到實現各種類型的神經網絡,本書解決了常見和不太常見的問題,以在分散環境中進行深度學習。此外,你還將獲得在Spark中可重複使用以解決類似問題或稍微不同問題的深度學習代碼。你還將學習如何使用Spark流式處理和聚類數據。一旦掌握了基礎知識,你將探索如何使用流行的庫(如TensorFlow和Keras)在Spark中實現和部署深度學習模型,例如卷積神經網絡(CNN)和循環神經網絡(RNN)。

通過閱讀本書,你將具備在Apache Spark上訓練和部署高效深度學習模型的專業知識。

你將學到:
- 設置完全功能的Spark環境
- 理解實用的機器學習和深度學習概念
- 在Spark內使用內建的機器學習庫
- 探索與TensorFlow和Keras兼容的庫
- 在Spark上探索Word2vec和TF-IDF等自然語言處理模型
- 為深度學習評估組織數據框
- 應用測試和訓練建模以確保準確性
- 存取可重複使用的現成代碼

本書適合對於使用Apache Spark實現高效分散式深度學習模型感興趣的讀者。為了更好地理解本書,需要具備核心機器學習概念的知識和對Apache Spark框架的基本理解。此外,具備Python編程知識將是一個加分項目。