 Название: Deep Learning Concepts in Operations Research
Автор: Biswadip Basu Mallik, Gunjan Mukherjee, Rahul Kar, Aryan Chaudhary
Издательство: CRC Press
Серия: Advances in Computational Collective Intelligence
Год: 2025
Страниц: 277
Язык: английский
Формат: pdf (true)
Размер: 29.2 MB
The model-based approach for carrying out classification and identification of tasks has led to the pervading progress of the Machine Learning (ML) 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 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.
Machine Learning has recently gained popularity in research and is used for a diversity of functions, together with content analysis, identifying spam, video inciting, picture dilution, and mixed media surface recovery. One of several Machine Learning calculations that is widely used in these applications is noteworthy learning (DL). One more name given to deep learning is representational learning. The best progress, such as in execution computing, which is making information obtaining capability intangible, may be the cause of the constant circulation of unneeded information within the ranges of important learning and dispersed learning. Deep Learning is derived from traditional neural networks, but is much more efficient than its predecessors. Also, Deep Learning uses both transformations and graphs to create multi-layered learning models. Recently developed DL techniques include sound and discourse handling, visual information preparation, common dialect handling (NLP), and the like.
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 Artificial Intelligence and Machine Learning. 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.
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