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Advances in Data Science and Computing Technology Methodology and Applications

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Advances in Data Science and Computing Technology Methodology and ApplicationsНазвание: Advances in Data Science and Computing Technology Methodology and Applications
Автор: Suman Ghosal, Amitava Choudhury
Издательство: CRC Press, Apple Academic Press, Inc.
Год: 2022
Страниц: 449
Язык: английский
Формат: pdf (true)
Размер: 41.9 MB

This volume helps to address the genuine 21st century need for advances in Data Science and Computing Technology. It provides an abundance of new research and studies on progressive and innovative technologies, including Artificial Intelligence (AI), communication systems, cyber security applications, data analytics, Internet of Things (IoT), Machine Learning (ML), power systems, VLSI, embedded systems, and much more. The book presents a variety of interesting and important aspects of Data Science and Computing Technologies and methodologies in a wide range of applications, including deep learning, DNA cryptography, classy fuzzy MPPT controller, driving assistance, and safety systems. Novel algorithms and their applications for solving cutting-edge computational and Data Science problems are included also for an interdisciplinary research perspective.

The book addresses recent applications of Deep Learning (DL) and ANN paradigms, the role and impact of Big Data in the e-commerce and retail sectors, algorithms for load balancing in cloud computing, advances in embedded system based applications, optimization techniques using a MATLAB platform, and techniques for improving information and network security.

Advances in Data Science and Computing Technology: Methodology and Applications provides a wealth of valuable information and food for thought on many important issues for data scientists and researchers, industry professionals, and faculty and students in the data and computing sciences.

This book consists of 26 chapters, covering discussion on innovative algorithms and their applications for solving cutting-edge computational and data science problems with an interdisciplinary research perspective. All 26 chapters are divided in following seven parts containing interdisciplinary applications and methodologies of Data Science and Computing Technologies:

Part I: Recent Application of Deep Learning and ANN Paradigm
Part II: Role and Impact of Big Data in E-Commerce and the Retail Sector
Part III: Algorithm for Load Balancing in Cloud Computing
Part IV: Advances in Embedded System-Based Applications
Part V: Optimization Technique Using MATLAB Platform
Part VI: Technique for Improving Information and Network Security
Part VII: Miscellaneous Topics in Computing

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