Deep Learning with R
暫譯: 使用 R 進行深度學習

Ghatak, Abhijit

Deep Learning with R
  • 出版商: Springer
  • 出版日期: 2020-05-02
  • 售價: $2,980
  • 貴賓價: 9.5 折 $2,831
  • 語言: 英文
  • 頁數: 390
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 9811370893
  • ISBN-13: 9789811370892
  • 相關分類: DeepLearning

    • 海外代購書籍(需單獨結帳)

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商品描述

Deep Learning with R introduces deep learning and neural networks using the R programming language. The book builds on the understanding of the theoretical and mathematical constructs and enables the reader to create applications on computer vision, natural language processing and transfer learning.

The book starts with an introduction to machine learning and moves on to describe the basic architecture, different activation functions, forward propagation, cross-entropy loss and backward propagation of a simple neural network. It goes on to create different code segments to construct deep neural networks. It discusses in detail the initialization of network parameters, optimization techniques, and some of the common issues surrounding neural networks such as dealing with NaNs and the vanishing/exploding gradient problem. Advanced variants of multilayered perceptrons namely, convolutional neural networks and sequence models are explained, followed by application to different use cases. The book makes extensive use of the Keras and TensorFlow frameworks.


商品描述(中文翻譯)

《使用 R 進行深度學習》介紹了使用 R 程式語言的深度學習和神經網絡。這本書建立在對理論和數學構造的理解之上，使讀者能夠創建計算機視覺、自然語言處理和遷移學習的應用。

本書首先介紹機器學習，然後描述基本架構、不同的激活函數、前向傳播、交叉熵損失和簡單神經網絡的反向傳播。接著，書中創建了不同的程式碼片段來構建深度神經網絡。它詳細討論了網絡參數的初始化、優化技術，以及一些與神經網絡相關的常見問題，例如處理 NaN 值和消失/爆炸梯度問題。書中解釋了多層感知器的進階變體，即卷積神經網絡和序列模型，並隨後應用於不同的使用案例。本書廣泛使用 Keras 和 TensorFlow 框架。

作者簡介

Abhijit Ghatak is a Data Scientist and holds an M.E. in Engineering and M.S. in Data Science from Stevens Institute of Technology, USA. He began his career as a submarine engineer officer in the Indian Navy and worked on various data-intensive projects involving submarine operations and construction. Thereafter he has worked in academia, technology companies and as a research scientist in the area of Internet of Things (IoT) and pattern recognition for the European Union (EU). He has published several papers in the areas of engineering and machine learning and is currently a consultant in the area of machine learning and deep learning. His research interests include IoT, stream analytics and design of deep learning systems.

作者簡介(中文翻譯)

Abhijit Ghatak 是一位資料科學家，擁有美國史蒂文斯理工學院的工程碩士（M.E.）和資料科學碩士（M.S.）學位。他的職業生涯始於印度海軍的潛艇工程軍官，參與了多個涉及潛艇操作和建造的數據密集型專案。此後，他在學術界、科技公司以及歐盟（EU）擔任研究科學家，專注於物聯網（IoT）和模式識別領域。他在工程和機器學習領域發表了多篇論文，目前擔任機器學習和深度學習領域的顧問。他的研究興趣包括物聯網、串流分析和深度學習系統的設計。

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