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Author: Olivas, Emilio Soria
Publisher: IGI Global
Published: 2009-08-31
Total Pages: 852
ISBN-13: 1605667676
DOWNLOAD EBOOK →"This book investiges machine learning (ML), one of the most fruitful fields of current research, both in the proposal of new techniques and theoretic algorithms and in their application to real-life problems"--Provided by publisher.
Author: Aboul Ella Hassanien
Publisher: Engineering Science Reference
Published: 2019
Total Pages: 0
ISBN-13: 9781522578628
DOWNLOAD EBOOK →"This book explores the application of deep learning in various areas like computer vision, image processing, biometrics, pattern recognition and medical imaging, and other real-world applications"--
Author: Hassanien, Aboul Ella
Publisher: IGI Global
Published: 2017-04-03
Total Pages: 1093
ISBN-13: 1522522301
DOWNLOAD EBOOK →Continuous improvements in technological applications have allowed more opportunities to develop automated systems. This not only leads to higher success in smart data analysis, but it increases the overall probability of technological progression. The Handbook of Research on Machine Learning Innovations and Trends is a key resource on the latest advances and research regarding the vast range of advanced systems and applications involved in machine intelligence. Highlighting multidisciplinary studies on decision theory, intelligent search, and multi-agent systems, this publication is an ideal reference source for professionals and researchers working in the field of machine learning and its applications.
Author: Solanki, Arun
Publisher: IGI Global
Published: 2019-12-13
Total Pages: 674
ISBN-13: 1522596453
DOWNLOAD EBOOK →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.
Author: Arun Solanki
Publisher:
Published: 2020
Total Pages: 710
ISBN-13: 9781523128884
DOWNLOAD EBOOK →"This book examines the role of machine learning in various applications such as data mining, natural language processing, image recognition, and expert systems"--.
Author: Karthik, S.
Publisher: IGI Global
Published: 2017-07-13
Total Pages: 265
ISBN-13: 1522530169
DOWNLOAD EBOOK →The expansion of digital data has transformed various sectors of business such as healthcare, industrial manufacturing, and transportation. A new way of solving business problems has emerged through the use of machine learning techniques in conjunction with big data analytics. Deep Learning Innovations and Their Convergence With Big Data is a pivotal reference for the latest scholarly research on upcoming trends in data analytics and potential technologies that will facilitate insight in various domains of science, industry, business, and consumer applications. Featuring extensive coverage on a broad range of topics and perspectives such as deep neural network, domain adaptation modeling, and threat detection, this book is ideally designed for researchers, professionals, and students seeking current research on the latest trends in the field of deep learning techniques in big data analytics.
Author: Sathiyamoorthi Velayutham
Publisher: IGI Global, Engineering Science Reference
Published: 2019-08-23
Total Pages: 0
ISBN-13: 9781522599050
DOWNLOAD EBOOK →"This book examines the practical applications and implementation of various machine learning techniques in various fields such as agriculture, medical, image processing, and networking"--
Author: Huang, Yi
Publisher: IGI Global
Published: 2021-09-24
Total Pages: 492
ISBN-13: 1799838218
DOWNLOAD EBOOK →With increasingly interconnected educational and employment ecosystems, credential innovations are trailblazing multiple pathways to professions at a pivotal moment of rapid change. In the current state of credential proliferation, the quest for simultaneous improvement of quality and value reflects heightened cross-sector interests, while at the same time the quest for concurrent enhancement of access and success remains. With the evolving educational models, technologies, and organizations, credential innovations will continue to serve as powerful catalysts in realizing the great promise for inclusive pathways to professions. The Handbook of Research on Credential Innovations for Inclusive Pathways to Professions surveys the state of credential innovations, examines trends and issues, and explores models and strategies with case studies across sectors and disciplines. The 21 chapters are organized in three sections. Section I, Credential Innovations Amid Evolving Ecosystems, features a powerful array of change theories-in-action with topics ranging from conceptual re-visioning to organizational restructuring and programmatic reengineering within evolving ecosystems. Section II, Credential Innovations and Propositions Across Sectors, spotlights diverse approaches to and propositions of credentials within complex socio-economic landscapes across education, business, and technology industries. Section III, Credential Innovation Models and Strategies, showcases institutional innovations ranging from model developments, pedagogical approaches, and personalized engagements to outcome measurements and strategies for sustainable implementation. Lessons learned and implications are explored to share promising practices, inform current development, and influence future policies toward inclusive excellence in education and the workplace.
Author: Hrnjica, Bahrudin
Publisher: IGI Global
Published: 2018-07-06
Total Pages: 310
ISBN-13: 1522560068
DOWNLOAD EBOOK →Data is more valuable than ever in the twenty-first century, and tremendous amounts of data are being generated every second. With a fast-growing information industry, engineers are required to develop new tools and techniques that increase human capabilities of mining useful knowledge from the vast amounts of data. Optimized Genetic Programming Applications: Emerging Research and Opportunities is an essential reference source that explores the concept of genetic programming and its role in managing engineering problems. It also examines genetic programming as a supervised machine learning technique, focusing on implementation and application. As a resource that details both the theoretical aspects and implementation of genetic programming, this book is a useful source for academicians, biological engineers, computer programmers, scientists, researchers, and upper-level students seeking the latest research on genetic programming.
Author: Milutinovi?, Veljko
Publisher: IGI Global
Published: 2022-03-11
Total Pages: 296
ISBN-13: 1799883523
DOWNLOAD EBOOK →Based on current literature and cutting-edge advances in the machine learning field, there are four algorithms whose usage in new application domains must be explored: neural networks, rule induction algorithms, tree-based algorithms, and density-based algorithms. A number of machine learning related algorithms have been derived from these four algorithms. Consequently, they represent excellent underlying methods for extracting hidden knowledge from unstructured data, as essential data mining tasks. Implementation of Machine Learning Algorithms Using Control-Flow and Dataflow Paradigms presents widely used data-mining algorithms and explains their advantages and disadvantages, their mathematical treatment, applications, energy efficient implementations, and more. It presents research of energy efficient accelerators for machine learning algorithms. Covering topics such as control-flow implementation, approximate computing, and decision tree algorithms, this book is an essential resource for computer scientists, engineers, students and educators of higher education, researchers, and academicians.
