Handbook of Research on New Investigations in Artificial Life, AI, and Machine Learning

Handbook of Research on New Investigations in Artificial Life, AI, and Machine Learning PDF

Author: Habib, Maki K.

Publisher: IGI Global

Published: 2022-02-25

Total Pages: 589

ISBN-13: 1799886875

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As technology spreads globally, researchers and scientists continue to develop and study the strategy behind creating artificial life. This research field is ever expanding, and it is essential to stay current in the contemporary trends in artificial life, artificial intelligence, and machine learning. This an important topic for researchers and scientists in the field as well as industry leaders who may adapt this technology. The Handbook of Research on New Investigations in Artificial Life, AI, and Machine Learning provides concepts, theories, systems, technologies, and procedures that exhibit properties, phenomena, or abilities of any living system or human. This major reference work includes the most up-to-date research on techniques and technologies supporting AI and machine learning. Covering topics such as behavior classification, quality control, and smart medical devices, it serves as an essential resource for graduate students, academicians, stakeholders, practitioners, and researchers and scientists studying artificial life, cognition, AI, biological inspiration, machine learning, and more.

Handbook of Research on Emerging Trends and Applications of Machine Learning

Handbook of Research on Emerging Trends and Applications of Machine Learning PDF

Author: Solanki, Arun

Publisher: IGI Global

Published: 2019-12-13

Total Pages: 674

ISBN-13: 1522596453

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As today’s world continues to advance, Artificial Intelligence (AI) is a field that has become a staple of technological development and led to the advancement of numerous professional industries. An application within AI that has gained attention is machine learning. Machine learning uses statistical techniques and algorithms to give computer systems the ability to understand and its popularity has circulated through many trades. Understanding this technology and its countless implementations is pivotal for scientists and researchers across the world. The Handbook of Research on Emerging Trends and Applications of Machine Learning provides a high-level understanding of various machine learning algorithms along with modern tools and techniques using Artificial Intelligence. In addition, this book explores the critical role that machine learning plays in a variety of professional fields including healthcare, business, and computer science. While highlighting topics including image processing, predictive analytics, and smart grid management, this book is ideally designed for developers, data scientists, business analysts, information architects, finance agents, healthcare professionals, researchers, retail traders, professors, and graduate students seeking current research on the benefits, implementations, and trends of machine learning.

Handbook of Research on Integrating Machine Learning Into HPC-based Simulations and Analytics

Handbook of Research on Integrating Machine Learning Into HPC-based Simulations and Analytics PDF

Author: Belgacem Ben Youssef

Publisher:

Published: 2023

Total Pages: 0

ISBN-13: 9781668437964

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"This edited book aims to present to the reader recent research efforts in designing and using ML techniques on HPC systems, discuss some of the results achieved thus far by cutting-edge relevant contributions. Another objective is to identify research challenges and opportunities in the area spanning the intersection of HPC and ML. In fact, further collaboration between the HPC and ML communities is encouraged for rapid and seamless progress toward an ecosystem that effectively serves both of these communities. Furthermore, new tools and benchmarks are required to overcome the common challenges across HPC and ML applications. The goals of this form of convergence are fourfold: 1. Obtain optimized solutions that show discernible reduction in compute requirements. 2. Facilitate having a more dynamic view of domain sciences. 3. Develop integrated knowledge through interdisciplinary collaboration. 4. Stimulate innovations with deep societal impact through the provisioning of new advances in scientific research spanning many application areas"--

Handbook of Research on Machine Learning

Handbook of Research on Machine Learning PDF

Author: Monika Mangla

Publisher: CRC Press

Published: 2022-08-04

Total Pages: 617

ISBN-13: 1000565726

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This volume takes the reader on a technological voyage of machine learning advancements, highlighting the systematic changes in algorithms, challenges, and constraints. The technological advancements in the ML arena have transformed and revolutionized several fields, including transportation, agriculture, finance, weather monitoring, and others. This book brings together researchers, authors, industrialists, and academicians to cover a vast selection of topics in ML, starting with the rudiments of machine learning approaches and going on to specific applications in healthcare and industrial automation. The book begins with an overview of the ethics, security and privacy issues, future directions, and challenges in machine learning as well as a systematic review of deep learning techniques and provides an understanding of building generative adversarial networks. Chapters explore predictive data analytics for health issues. The book also adds a macro dimension by highlighting the industrial applications of machine learning, such as in the steel industry, for urban information retrieval, in garbage detection, in measuring air pollution, for stock market predictions, for underwater fish detection, as a fake news predictor, and more.

Handbook of Research on Machine Learning Techniques for Pattern Recognition and Information Security

Handbook of Research on Machine Learning Techniques for Pattern Recognition and Information Security PDF

Author: Dua, Mohit

Publisher: IGI Global

Published: 2021-05-14

Total Pages: 355

ISBN-13: 1799833011

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The artificial intelligence subset machine learning has become a popular technique in professional fields as many are finding new ways to apply this trending technology into their everyday practices. Two fields that have majorly benefited from this are pattern recognition and information security. The ability of these intelligent algorithms to learn complex patterns from data and attain new performance techniques has created a wide variety of uses and applications within the data security industry. There is a need for research on the specific uses machine learning methods have within these fields, along with future perspectives. The Handbook of Research on Machine Learning Techniques for Pattern Recognition and Information Security is a collection of innovative research on the current impact of machine learning methods within data security as well as its various applications and newfound challenges. While highlighting topics including anomaly detection systems, biometrics, and intrusion management, this book is ideally designed for industrial experts, researchers, IT professionals, network developers, policymakers, computer scientists, educators, and students seeking current research on implementing machine learning tactics to enhance the performance of information security.

Handbook of Deep Learning Applications

Handbook of Deep Learning Applications PDF

Author: Valentina Emilia Balas

Publisher: Springer

Published: 2019-02-25

Total Pages: 383

ISBN-13: 3030114791

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This book presents a broad range of deep-learning applications related to vision, natural language processing, gene expression, arbitrary object recognition, driverless cars, semantic image segmentation, deep visual residual abstraction, brain–computer interfaces, big data processing, hierarchical deep learning networks as game-playing artefacts using regret matching, and building GPU-accelerated deep learning frameworks. Deep learning, an advanced level of machine learning technique that combines class of learning algorithms with the use of many layers of nonlinear units, has gained considerable attention in recent times. Unlike other books on the market, this volume addresses the challenges of deep learning implementation, computation time, and the complexity of reasoning and modeling different type of data. As such, it is a valuable and comprehensive resource for engineers, researchers, graduate students and Ph.D. scholars.

Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry

Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry PDF

Author: Chkoniya, Valentina

Publisher: IGI Global

Published: 2021-06-25

Total Pages: 653

ISBN-13: 1799869865

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The contemporary world lives on the data produced at an unprecedented speed through social networks and the internet of things (IoT). Data has been called the new global currency, and its rise is transforming entire industries, providing a wealth of opportunities. Applied data science research is necessary to derive useful information from big data for the effective and efficient utilization to solve real-world problems. A broad analytical set allied with strong business logic is fundamental in today’s corporations. Organizations work to obtain competitive advantage by analyzing the data produced within and outside their organizational limits to support their decision-making processes. This book aims to provide an overview of the concepts, tools, and techniques behind the fields of data science and artificial intelligence (AI) applied to business and industries. The Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry discusses all stages of data science to AI and their application to real problems across industries—from science and engineering to academia and commerce. This book brings together practice and science to build successful data solutions, showing how to uncover hidden patterns and leverage them to improve all aspects of business performance by making sense of data from both web and offline environments. Covering topics including applied AI, consumer behavior analytics, and machine learning, this text is essential for data scientists, IT specialists, managers, executives, software and computer engineers, researchers, practitioners, academicians, and students.