Deep Learning Concepts in Operations Research (Hardcover)

Biswadip Basu Mallik

ISBN 10: 1032553790 / ISBN 13: 9781032553795

Editore: Taylor & Francis Ltd, London, 2024

Riguardo questo articolo

Hardcover. The model-based approach for carrying out classification and identification of tasks has led to the pervading progress of the machine learning paradigm in diversified fields of technology. Deep Learning Concepts in Operations Research looks at the concepts that are the foundation of this model-based approach. Apart from the classification process, the machine learning (ML) model has become effective enough to predict future trends of any sort of phenomena. Such fields as object classification, speech recognition, and face detection have sought extensive application of artificial intelligence (AI) and ML as well. Among a variety of topics, the book examines:An overview of applications and computing devicesDeep learning impacts in the field of AIDeep learning as state-of-the-art approach to AIExploring deep learning architecture for cutting-edge AI solutionsOperations research is the branch of mathematics for performing many operational tasks in other allied domains, and the book explains how the implementation of automated strategies in optimization and parameter selection can be carried out by AI and ML. Operations research has many beneficial aspects for decision making. Discussing how a proper decision depends on several factors, the book examines how AI and ML can be used to model equations and define constraints to solve problems and discover proper and valid solutions more easily. It also looks at how automation plays a significant role in minimizing human labor and thereby minimizes overall time and cost. The book provides mathematicians an overview of AI and machine learning relevant to operations research. It focuses decision modeling and optimization models as well as algorithms. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Codice articolo 9781032553795

Dati bibliografici

• Titolo: Deep Learning Concepts in Operations Research (Hardcover)
• Editore: Taylor & Francis Ltd, London
• Data di pubblicazione: 2024
• Lingua: Inglese
• ISBN 10: 1032553790
• ISBN 13: 9781032553795
• Rilegatura: Hardcover
• Condizione: new

Descrizione articolo

Riassunto

The model-based approach for carrying out classification and identification of tasks has led to the pervading progress of the machine learning paradigm in diversified fields of technology. Deep Learning Concepts in Operations Research looks at the concepts that are the foundation of this model-based approach. Apart from the classification process, the machine learning (ML) model has become effective enough to predict future trends of any sort of phenomena. Such fields as object classification, speech recognition, and face detection have sought extensive application of artificial intelligence (AI) and ML as well. Among a variety of topics, the book examines:

• An overview of applications and computing devices
• Deep learning impacts in the field of AI
• Deep learning as state-of-the-art approach to AI
• Exploring deep learning architecture for cutting-edge AI solutions

Operations research is the branch of mathematics for performing many operational tasks in other allied domains, and the book explains how the implementation of automated strategies in optimization and parameter selection can be carried out by AI and ML. Operations research has many beneficial aspects for decision making. Discussing how a proper decision depends on several factors, the book examines how AI and ML can be used to model equations and define constraints to solve problems and discover proper and valid solutions more easily. It also looks at how automation plays a significant role in minimizing human labor and thereby minimizes overall time and cost.

Informazioni sull?autore

Dr. Biswadip Basu Mallik is an associate professor of Mathematics in the Department of Basic Science & Humanities at Institute of Engineering & Management, University of Engineering & Management, Kolkata, India.

Dr. Gunjan Mukherjee is an associate professor in the Department of Computational Science, Brainware University, Barasat, India.

Rahul Kar holds a master's degree in mathematics from Burdwan University and is currently working as a SACT-II Mathematics faculty of Kalyani Mahavidyalaya, Kalyani, Nadia, West Bengal.

Aryan Chaudhary is the chief scientific advisor at BioTech Sphere Research, India, and a recognized researcher of healthcare and technology.