Industrial Applications of Machine Learning
暫譯: 機器學習在工業應用中的應用
Larrañaga, Pedro, Atienza, David, Diaz-Rozo, Javier
- 出版商: CRC
- 出版日期: 2020-09-30
- 售價: $2,350
- 貴賓價: 9.5 折 $2,233
- 語言: 英文
- 頁數: 336
- 裝訂: Quality Paper - also called trade paper
- ISBN: 0367656876
- ISBN-13: 9780367656874
-
相關分類:
Machine Learning
海外代購書籍(需單獨結帳)
商品描述
Industrial Applications of Machine Learning shows how machine learning can be applied to address real-world problems in the fourth industrial revolution, and provides the required knowledge and tools to empower readers to build their own solutions based on theory and practice. The book introduces the fourth industrial revolution and its current impact on organizations and society. It explores machine learning fundamentals, and includes four case studies that address a real-world problem in the manufacturing or logistics domains, and approaches machine learning solutions from an application-oriented point of view. The book should be of special interest to researchers interested in real-world industrial problems.
Features
- Describes the opportunities, challenges, issues, and trends offered by the fourth industrial revolution
- Provides a user-friendly introduction to machine learning with examples of cutting-edge applications in different industrial sectors
- Includes four case studies addressing real-world industrial problems solved with machine learning techniques
- A dedicated website for the book contains the datasets of the case studies for the reader's reproduction, enabling the groundwork for future problem-solving
- Uses of three of the most widespread software and programming languages within the engineering and data science communities, namely R, Python, and Weka
商品描述(中文翻譯)
《機器學習的工業應用》展示了機器學習如何應用於解決第四次工業革命中的現實問題,並提供所需的知識和工具,讓讀者能夠根據理論和實踐建立自己的解決方案。本書介紹了第四次工業革命及其對組織和社會的當前影響。它探討了機器學習的基本原理,並包括四個案例研究,針對製造或物流領域中的現實問題,從應用導向的角度探討機器學習解決方案。本書對於對現實工業問題感興趣的研究人員特別有吸引力。
特點
- 描述了第四次工業革命所帶來的機會、挑戰、問題和趨勢
- 提供了機器學習的友好入門,並舉例說明不同工業領域中的尖端應用
- 包含四個案例研究,針對使用機器學習技術解決的現實工業問題
- 本書專用網站包含案例研究的數據集,供讀者重現,為未來的問題解決奠定基礎
- 使用三種在工程和數據科學社群中最廣泛使用的軟體和程式語言,即 R、Python 和 Weka