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Handbook of Machine Learning for Computational Optimization

Applications and Case Studies

Vishal Jain editor Sapna Juneja editor Abhinav Juneja editor Ramani Kannan editor

Format:Hardback

Publisher:Taylor & Francis Ltd

Published:3rd Nov '21

Currently unavailable, and unfortunately no date known when it will be back

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Handbook of Machine Learning for Computational Optimization cover

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.

ISBN: 9780367685423

Dimensions: unknown

Weight: 535g

280 pages