Machine learning and artificial intelligence with industrial applications from big data to small data / [electronic resource] :

• 其他作者：
  • Carou, Diego.
  • Sartal, Antonio.
  • Davim, J. Paulo.
  • SpringerLink (Online service)
• 其他題名：
  • Management and industrial engineering.
• 出版： Cham : Springer International Publishing :Imprint: Springer
• 叢書名： Management and industrial engineering,
• 主題： Machine learning--Industrial applications. , Artificial intelligence--Industrial applications. , Industrial and Production Engineering. , Machine Learning. , Artificial Intelligence.
• ISBN： 9783030910068 (electronic bk.) 、 9783030910051 (paper)
• FIND@SFXID: CGU
• 資料類型: 電子書
• 內容註: A Note on Big Data and Value Creation -- Modern Machine Learning: Applications and Methods -- Decision Support System Based on Deep Learning for Improving The Quality Control Task of Rifles: A Case Study In Industry 4.0 -- Title: Ml & Ai Application for The Automotive Industry -- Application of Machine Learning and Big-Data Techniques to Quality Control and Food Safety In The Industrial Production of Food and Beverages.
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• 摘要註: This book presents the tools used in machine learning (ML) and the benefits of using such tools in facilities. It focus on real life business applications, explaining the most popular algorithms easily and clearly without the use of calculus or matrix/vector algebra. Replete with case studies, this book provides a working knowledge of ML current and future capabilities and the impact it will have on every business. It demonstrates that it is also possible to carry out successful ML and AI projects in any manufacturing plant, even without fully fulfilling the five V (Volume, Velocity, Variety, Veracity and Value) usually associated with big data. This book takes a closer look at how AI and ML are also able to work for industrial area, as well as how you could adapt some of the standard tips and techniques (usually for big data) for your own needs in your SME. Organizations which first understand these tools and know how to use them will benefit at the expense of their rivals.
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