BIBFRAME Work

Title

Handbook of machine learning for computational optimization : applications and case studies

Type

  • Text
  • Monograph

Contribution

Subject

  • Mathematical optimization--Data processing (LCSH)
  • Machine learning--Industrial applications (LCSH)
  • Artificial intelligence (LCSH)

Language

Illustrative Content

Classification

Content

Supplementary content

Summary

"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 which 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"-- Provided by publisher.

Authorized Access Point

Handbook of machine learning for computational optimization : applications and case studies

Admin Metadata

  • Date: 2026-09-11T20:20:44.650395+00:00
  • Agent: cbc
  • Status: c
  • Derived from: 21992357

Admin Metadata

  • Date: 2026-09-11
  • Cataloger id: Unknown
  • Description level: http://id.loc.gov/ontologies/bibframe-2-6-0/
  • Description language: eng
  • Description authentication: pcc

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