6Pattern Recognition Applications in Distributed Systems and Distributed Machine Learning
Kalyani S.1*, Swarup K. S.2, Sandhya Avasthi3 and Tanushree Sanwal4
1Subject Matter Expert (Electrical), L&TEduTech, Larsen & Toubro Limited, Chennai, Tamilnadu, India
2Department of Electrical Engineering, Indian Institute of Technology Madras, Chennai, India
3Department of CSE, ABES Engineering College, Ghaziabad, Uttar Pradesh, India
4KIET Group of Institutions Delhi-NCR, Ghaziabad, India
Abstract
Identifying patterns and structures within data constitutes a fundamental problem across various disciplines, facilitating informed decision-making processes. Distributed computing has emerged as a crucial enabling technology to effectively solve these challenges. The reason for this phenomenon can be attributed to the rapid growth of data and the intricate nature of modern pattern recognition algorithms. Distributed computing harnesses the collective computational capabilities of numerous interconnected nodes to facilitate the parallel processing and analysis of large datasets. This methodology provides scalable, efficient, and prompt resolutions for issues pertaining to pattern recognition. As the data grow for pattern recognition application, efficient machine learning techniques are need to process such huge data in a distributed manner. Distributed system, a powerful technology, is formed by multi-computers connected via a network and communicate with each other and share their hardware ...
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