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Download the fantastic book titled Optimization in Machine Learning and Applications written by Anand J. Kulkarni, available in its entirety in both PDF and EPUB formats for online reading. This page includes a concise summary, a preview of the book cover, and detailed information about "Optimization in Machine Learning and Applications", which was released on 29 November 2019. We suggest perusing the summary before initiating your download. This book is a top selection for enthusiasts of the Technology & Engineering genre.

Summary of Optimization in Machine Learning and Applications by Anand J. Kulkarni PDF

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 in Machine Learning and Applications

Detail About Optimization in Machine Learning and Applications PDF

  • Author : Anand J. Kulkarni
  • Publisher : Springer Nature
  • Genre : Technology & Engineering
  • Total Pages : 202 pages
  • ISBN : 9811509948
  • PDF File Size : 32,7 Mb
  • Language : English
  • Rating : 4/5 from 21 reviews

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Optimization in Machine Learning and Applications

Optimization in Machine Learning and Applications
  • Publisher : Springer Nature
  • File Size : 55,9 Mb
  • Release Date : 29 November 2019
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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 discusses the optimization methods that help

Optimization

Optimization
  • Publisher : CRC Press
  • File Size : 31,8 Mb
  • Release Date : 06 May 2015
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Choose the Correct Solution Method for Your Optimization ProblemOptimization: Algorithms and Applications presents a variety of solution techniques for optimization problems, emphasizing concepts rather than rigorous mathematical details and proofs.

Machine Learning Algorithms and Applications

Machine Learning Algorithms and Applications
  • Publisher : John Wiley & Sons
  • File Size : 40,9 Mb
  • Release Date : 24 August 2021
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Machine Learning Algorithms is for current and ambitious machine learning specialists looking to implement solutions to real-world machine learning problems. It talks entirely about the various applications of machine and

Optimization, Learning Algorithms and Applications

Optimization, Learning Algorithms and Applications
  • Publisher : Springer Nature
  • File Size : 50,6 Mb
  • Release Date : 01 January 2023
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This book constitutes the proceedings of the Second International Conference on Optimization, Learning Algorithms and Applications, OL2A 2022, held in Bragança, Portugal, in October 2022. The 53 full papers and 3 short

Optimization, Learning Algorithms and Applications

Optimization, Learning Algorithms and Applications
  • Publisher : Springer Nature
  • File Size : 45,8 Mb
  • Release Date : 02 December 2021
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This book constitutes selected and revised papers presented at the First International Conference on Optimization, Learning Algorithms and Applications, OL2A 2021, held in Bragança, Portugal, in July 2021. Due to

Distributed Optimization, Game and Learning Algorithms

Distributed Optimization, Game and Learning Algorithms
  • Publisher : Springer Nature
  • File Size : 23,8 Mb
  • Release Date : 04 January 2021
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This book provides the fundamental theory of distributed optimization, game and learning. It includes those working directly in optimization,-and also many other issues like time-varying topology, communication delay, equality

Approximation and Optimization

Approximation and Optimization
  • Publisher : Springer
  • File Size : 47,7 Mb
  • Release Date : 10 May 2019
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This book focuses on the development of approximation-related algorithms and their relevant applications. Individual contributions are written by leading experts and reflect emerging directions and connections in data approximation and

Machine Learning

Machine Learning
  • Publisher : BoD – Books on Demand
  • File Size : 20,8 Mb
  • Release Date : 22 December 2021
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Recent times are witnessing rapid development in machine learning algorithm systems, especially in reinforcement learning, natural language processing, computer and robot vision, image processing, speech, and emotional processing and understanding.

Optimization, Learning Algorithms and Applications

Optimization, Learning Algorithms and Applications
  • Publisher : Unknown Publisher
  • File Size : 32,7 Mb
  • Release Date : 17 June 2024
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This book constitutes selected and revised papers presented at the First International Conference on Optimization, Learning Algorithms and Applications, OL2A 2021, held in Bragança, Portugal, in July 2021. Due to

Metaheuristics for Machine Learning

Metaheuristics for Machine Learning
  • Publisher : John Wiley & Sons
  • File Size : 40,6 Mb
  • Release Date : 28 March 2024
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METAHEURISTICS for MACHINE LEARNING The book unlocks the power of nature-inspired optimization in machine learning and presents a comprehensive guide to cutting-edge algorithms, interdisciplinary insights, and real-world applications. The field