R Deep Learning Cookbook

Dr. PKS Prakash, Achyutuni Sri Krishna Rao

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商品描述

Key Features

  • Master intricacies of R deep learning packages such as mxnet & tensorflow
  • Learn application on deep learning in different domains using practical examples from text, image and speech
  • Guide to set-up deep learning models using CPU and GPU

Book Description

Deep Learning is the next big thing. It is a part of machine learning. Its favorable results in application with huge and complex data is remarkable. Simultaneously, R programming language is very popular amongst the data miners and statisticians. With the growth in Deep Learning, the inter relation between R and deep learning is growing tremendously as they are very compatible with each other in attaining the various results.

This book will help you to get through the problems that you face during the execution of different tasks and Understand hacks in deep learning, neural networks, and advanced machine learning techniques. It will also take you through complex deep learning algorithms and various deep learning packages and libraries in R. It will be starting with different packages in Deep Learning to neural networks and structures. You will also encounter the applications in text mining and processing along with comparison between CPU and GPU performance.

By the end of the book, you will have a logical understanding of Deep learning and different deep learning packages to have the most appropriate solutions for your problems.

What you will learn

  • Build deep learning models in different application areas using H20, MXnet.
  • Analyzing a Deep boltzmann machine
  • Setting up and Analysing Deep belief networks
  • Generating a RNN-RBM hybrid model for sequence generation
  • Building supervised model using various machine learning algorithms
  • Set up variants of basic convolution function
  • Represent data using Autoencoders.
  • Explore generative models available in Deep Learning.
  • Implement Branching Program Machines for structured or sequential outputs
  • Discover sequence modeling using Recurrent and Recursive nets
  • Learn the steps involved in applying Deep Learning in text mining
  • Train a deep learning model on a GPU

商品描述(中文翻譯)

主要特點


  • 掌握 R 深度學習套件(如 mxnet 和 tensorflow)的細節

  • 通過實際範例學習在文本、圖像和語音等不同領域應用深度學習

  • 指導如何使用 CPU 和 GPU 設置深度學習模型

書籍描述

深度學習是下一個大趨勢,它是機器學習的一部分。在處理龐大且複雜的數據時,它展現出令人驚嘆的效果。與此同時,R 程式語言在數據挖掘和統計學家中非常受歡迎。隨著深度學習的發展,R 和深度學習之間的相互關係也在迅速增長,因為它們在實現各種結果方面非常相容。

本書將幫助您解決在執行不同任務時遇到的問題,並了解深度學習、神經網絡和高級機器學習技術的技巧。它還將帶您深入了解複雜的深度學習算法以及 R 中的各種深度學習套件和庫。從深度學習的不同套件到神經網絡和結構,您將遇到文本挖掘和處理的應用,並比較 CPU 和 GPU 的性能。

通過閱讀本書,您將對深度學習和不同的深度學習套件有一個邏輯上的理解,以便為您的問題找到最合適的解決方案。

您將學到什麼


  • 使用 H20、MXnet 在不同應用領域構建深度學習模型

  • 分析深度玻爾茨曼機

  • 設置和分析深度置信網絡

  • 生成用於序列生成的 RNN-RBM 混合模型

  • 使用各種機器學習算法構建監督模型

  • 設置基本卷積函數的變體

  • 使用自編碼器表示數據

  • 探索深度學習中的生成模型

  • 實現用於結構化或序列輸出的分支程序機器

  • 使用循環和遞歸網絡進行序列建模

  • 學習在文本挖掘中應用深度學習的步驟

  • 在 GPU 上訓練深度學習模型