Optimization in Machine Learning and Applications

  • Anand J. Kulkarni
  • Suresh Chandra Satapathy

Part of the Algorithms for Intelligent Systems book series (AIS)

Table of contents

  1. Front Matter
    Pages i-ix
  2. Prachi R. Rajarapollu, Debashis Adhikari, Nutan V. Bansode
    Pages 1-12
  3. Sankar N. Nair, E. S. Gopi
    Pages 13-29
  4. Souad Taleb Zouggar, Abdelkader Adla
    Pages 31-50
  5. Mrunalini Jadhav, Kanchan Khare, Sayali Apte, Rushikesh Kulkarni
    Pages 69-89
  6. Santosh Kumar Biswal, Nikhil Kumar Gouda
    Pages 155-167
  7. Back Matter
    Pages 197-197

About this book


This book discusses one of the major applications of artificial intelligence: the use of machine learning to extract useful information from multimodal data. It discusses the optimization methods that help minimize the error in developing patterns and classifications, which further helps improve prediction and decision-making. The book also presents formulations of real-world machine learning problems, and discusses AI solution methodologies as standalone or hybrid approaches. Lastly, it proposes novel metaheuristic methods to solve complex machine learning problems. Featuring valuable insights, the book helps readers explore new avenues leading toward multidisciplinary research discussions.


Optimization Machine Learning Metaheuristics Heuristics Classification

Editors and affiliations

  • Anand J. Kulkarni
    • 1
  • Suresh Chandra Satapathy
    • 2
  1. 1.Department of Mechanical EngineeringSymbiosis Institute of TechnologyPuneIndia
  2. 2.School of Computer EngineeringKalinga Institute of Industrial Technology (KIIT)BhubaneswarIndia

Bibliographic information

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