Handbook of Machine Learning for Computational Optimization

Handbook of Machine Learning for Computational Optimization
Author: Vishal Jain
Publisher: CRC Press
Total Pages: 295
Release: 2021-11-02
Genre: Business & Economics
ISBN: 100045567X

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Technology is moving at an exponential pace in this era of computational intelligence. Machine learning has emerged as one of the most promising tools used to challenge and think beyond current limitations. This handbook will provide readers with a leading edge to improving their products and processes through optimal and smarter machine learning techniques. This handbook focuses on new machine learning developments that can lead to newly developed applications. It uses a predictive and futuristic approach, which makes machine learning a promising tool for processes and sustainable solutions. It also promotes newer algorithms that are more efficient and reliable for new dimensions in discovering other applications, and then goes on to discuss the potential in making better use of machines in order to ensure optimal prediction, execution, and decision-making. Individuals looking for machine learning-based knowledge will find interest in this handbook. The readership ranges from undergraduate students of engineering and allied courses to researchers, professionals, and application designers.


Handbook of Machine Learning for Computational Optimization
Language: en
Pages: 297
Authors: Vishal Jain
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Type: BOOK - Published: 2021-11-02 - Publisher: CRC Press

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This book discusses one of the major applications of artificial intelligence: the use of machine learning to extract useful information from multimodal data. It
Handbook of Machine Learning for Computational Optimization
Language: en
Pages: 295
Authors: Vishal Jain
Categories: Business & Economics
Type: BOOK - Published: 2021-11-02 - Publisher: CRC Press

GET EBOOK

Technology is moving at an exponential pace in this era of computational intelligence. Machine learning has emerged as one of the most promising tools used to c
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Pages: 509
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An up-to-date account of the interplay between optimization and machine learning, accessible to students and researchers in both communities. The interplay betw