Machine Learning and Big Data Analytics (Proceedings of International Conference on Machine Learning and Big Data Analytics (ICMLBDA) 2021)
Machine Learning and Big Data Analytics (Proceedings of International Conference on Machine Learning and Big Data Analytics (ICMLBDA) 2021)

Author: Rajiv Misra

Publisher: Springer Nature

Published: 2021-09-29

Total Pages: 362

ISBN-13: 3030824691

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This edited volume on machine learning and big data analytics (Proceedings of ICMLBDA 2021) is intended to be used as a reference book for researchers and practitioners in the disciplines of computer science, electronics and telecommunication, information science, and electrical engineering. Machine learning and Big data analytics represent a key ingredients in the industrial applications for new products and services. Big data analytics applies machine learning for predictions by examining large and varied data sets—i.e., big data—to uncover hidden patterns, unknown correlations, market trends, customer preferences, and other useful information that can help organizations make more informed business decisions.

Machine Learning and Big Data Analytics
Machine Learning and Big Data Analytics

Author: Rajiv Misra

Publisher: Springer Nature

Published: 2023-06-06

Total Pages: 552

ISBN-13: 3031151755

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This edited volume on machine learning and big data analytics (Proceedings of ICMLBDA 2022) is intended to be used as a reference book for researchers and professionals to share their research and reports of new technologies and applications in Machine Learning and Big Data Analytics like biometric Recognition Systems, medical diagnosis, industries, telecommunications, AI Petri Nets Model-Based Diagnosis, gaming, stock trading, Intelligent Aerospace Systems, robot control, law, remote sensing and scientific discovery agents and multiagent systems; and natural language and Web intelligence. The intent of this book is to provide awareness of algorithms used for machine learning and big data in the advanced Scientific Technologies, provide a correlation of multidisciplinary areas and become a point of great interest for Data Scientists, systems architects, developers, new researchers and graduate level students. This volume provides cutting-edge research from around the globe on this field. Current status, trends, future directions, opportunities, etc. are discussed, making it friendly for beginners and young researchers.

AI-Driven Innovations in Digital Healthcare: Emerging Trends, Challenges, and Applications
AI-Driven Innovations in Digital Healthcare: Emerging Trends, Challenges, and Applications

Author: Khang, Alex

Publisher: IGI Global

Published: 2024-02-09

Total Pages: 393

ISBN-13:

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Within the healthcare sector, a pressing need for transformative changes is growing. From chronic diseases to complex diagnostic procedures, the industry stands at the crossroads of technological innovation and a burgeoning demand for more efficient, precise interventions. Patient expectations are soaring, and the deluge of medical data is overwhelming traditional healthcare systems. It is within this challenging environment that AI-Driven Innovations in Digital Healthcare: Emerging Trends, Challenges, and Applications emerges as a beacon of insight and practical solutions. The traditional healthcare framework is struggling to keep pace with the diverse demands of patients and the ever-expanding volume of medical data. As diseases become more intricate, attempts to provide timely identification and precise treatment of ailments become increasingly elusive. The urgency for a paradigm shift in healthcare delivery is emphasized by the critical need for early interventions, particularly in disease prediction. This challenge necessitates a holistic approach that harnesses the power of artificial intelligence (AI) and innovative technologies to steer healthcare toward a more responsive and patient-centric future.

Data Science, Analytics and Machine Learning with R
Data Science, Analytics and Machine Learning with R

Author: Luiz Paulo Favero

Publisher: Academic Press

Published: 2023-01-23

Total Pages: 662

ISBN-13: 0323859232

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Data Science, Analytics and Machine Learning with R explains the principles of data mining and machine learning techniques and accentuates the importance of applied and multivariate modeling. The book emphasizes the fundamentals of each technique, with step-by-step codes and real-world examples with data from areas such as medicine and health, biology, engineering, technology and related sciences. Examples use the most recent R language syntax, with recognized robust, widespread and current packages. Code scripts are exhaustively commented, making it clear to readers what happens in each command. For data collection, readers are instructed how to build their own robots from the very beginning. In addition, an entire chapter focuses on the concept of spatial analysis, allowing readers to build their own maps through geo-referenced data (such as in epidemiologic research) and some basic statistical techniques. Other chapters cover ensemble and uplift modeling and GLMM (Generalized Linear Mixed Models) estimations, both linear and nonlinear. - Presents a comprehensive and practical overview of machine learning, data mining and AI techniques for a broad multidisciplinary audience - Serves readers who are interested in statistics, analytics and modeling, and those who wish to deepen their knowledge in programming through the use of R - Teaches readers how to apply machine learning techniques to a wide range of data and subject areas - Presents data in a graphically appealing way, promoting greater information transparency and interactive learning

Machine Learning and Big Data Analytics Paradigms: Analysis, Applications and Challenges
Machine Learning and Big Data Analytics Paradigms: Analysis, Applications and Challenges

Author: Aboul Ella Hassanien

Publisher: Springer Nature

Published: 2020-12-14

Total Pages: 648

ISBN-13: 303059338X

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This book is intended to present the state of the art in research on machine learning and big data analytics. The accepted chapters covered many themes including artificial intelligence and data mining applications, machine learning and applications, deep learning technology for big data analytics, and modeling, simulation, and security with big data. It is a valuable resource for researchers in the area of big data analytics and its applications.

Proceedings of the International Conference on Big Data, IoT, and Machine Learning
Proceedings of the International Conference on Big Data, IoT, and Machine Learning

Author: Mohammad Shamsul Arefin

Publisher: Springer Nature

Published: 2021-12-03

Total Pages: 784

ISBN-13: 9811666369

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This book gathers a collection of high-quality peer-reviewed research papers presented at the International Conference on Big Data, IoT and Machine Learning (BIM 2021), held in Cox’s Bazar, Bangladesh, during 23–25 September 2021. The book covers research papers in the field of big data, IoT and machine learning. The book will be helpful for active researchers and practitioners in the field.

Advances in Machine Learning and Big Data Analytics II
Advances in Machine Learning and Big Data Analytics II

Author: Ashokkumar Patel

Publisher: Springer

Published: 2024-06-20

Total Pages: 0

ISBN-13: 9783031513411

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In the dynamic landscape of technology, machine learning and big data analytics have emerged as transformative forces, reshaping industries and empowering innovation. Machine learning, a subset of artificial intelligence, equips systems to learn and adapt from data, revolutionizing decision-making, automation, and predictive capabilities. Meanwhile, Big Data Analytics processes and extracts insights from vast and complex datasets, unveiling hidden patterns and trends. Together, these fields enable us to harness the immense power of data for smarter business strategies, improved healthcare, enhanced user experiences, and countless other applications. This edited volume on machine learning and big data analytics (Proceedings of ICMLBDA 2023, which was held on May 29-30, 2023 by NERIST and NIT Arunachal Pradesh India) introduces an exciting journey into the intersection of machine learning and Big Data Analytics, where data becomes a catalyst for progress and transformation.

CISA – Certified Information Systems Auditor Study Guide
CISA – Certified Information Systems Auditor Study Guide

Author: Hemang Doshi

Publisher: Packt Publishing Ltd

Published: 2020-08-21

Total Pages: 580

ISBN-13: 183898531X

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This CISA study guide is for those interested in achieving CISA certification and provides complete coverage of ISACA's latest CISA Review Manual (2019) with practical examples and over 850 exam-oriented practice questions Key Features Book DescriptionAre you looking to prepare for the CISA exam and understand the roles and responsibilities of an information systems (IS) auditor? The CISA - Certified Information Systems Auditor Study Guide is here to help you get started with CISA exam prep. This book covers all the five CISA domains in detail to help you pass the exam. You’ll start by getting up and running with the practical aspects of an information systems audit. The book then shows you how to govern and manage IT, before getting you up to speed with acquiring information systems. As you progress, you’ll gain knowledge of information systems operations and understand how to maintain business resilience, which will help you tackle various real-world business problems. Finally, you’ll be able to assist your organization in effectively protecting and controlling information systems with IT audit standards. By the end of this CISA book, you'll not only have covered the essential concepts and techniques you need to know to pass the CISA certification exam but also have the ability to apply them in the real world.What you will learn Understand the information systems auditing process Get to grips with IT governance and management Gain knowledge of information systems acquisition Assist your organization in protecting and controlling information systems with IT audit standards Understand information systems operations and how to ensure business resilience Evaluate your organization’s security policies, standards, and procedures to meet its objectives Who this book is for This CISA exam study guide is designed for those with a non-technical background who are interested in achieving CISA certification and are currently employed or looking to gain employment in IT audit and security management positions.