Handbook Of Research On Deep Learning Innovations And Trends


Handbook Of Research On Deep Learning Innovations And Trends
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Handbook Of Research On Deep Learning Innovations And Trends


Handbook Of Research On Deep Learning Innovations And Trends
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Author : Aboul Ella Hassanien
language : en
Publisher: Engineering Science Reference
Release Date : 2019

Handbook Of Research On Deep Learning Innovations And Trends written by Aboul Ella Hassanien and has been published by Engineering Science Reference this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with Artificial intelligence categories.


"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"--



Handbook Of Research On Machine Learning Applications And Trends Algorithms Methods And Techniques


Handbook Of Research On Machine Learning Applications And Trends Algorithms Methods And Techniques
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Author : Olivas, Emilio Soria
language : en
Publisher: IGI Global
Release Date : 2009-08-31

Handbook Of Research On Machine Learning Applications And Trends Algorithms Methods And Techniques written by Olivas, Emilio Soria and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-08-31 with Computers categories.


"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.



Handbook Of Research On Machine Learning Innovations And Trends Vol 2


Handbook Of Research On Machine Learning Innovations And Trends Vol 2
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Author : Tarek Gaber
language : en
Publisher:
Release Date : 2017-03-27

Handbook Of Research On Machine Learning Innovations And Trends Vol 2 written by Tarek Gaber and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-27 with categories.




Handbook Of Research On Emerging Trends And Applications Of Machine Learning


Handbook Of Research On Emerging Trends And Applications Of Machine Learning
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Author : Solanki, Arun
language : en
Publisher: IGI Global
Release Date : 2019-12-13

Handbook Of Research On Emerging Trends And Applications Of Machine Learning written by Solanki, Arun and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-13 with Computers categories.


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 Machine Learning Innovations And Trends


Handbook Of Research On Machine Learning Innovations And Trends
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Author : Hassanien, Aboul Ella
language : en
Publisher: IGI Global
Release Date : 2017-04-03

Handbook Of Research On Machine Learning Innovations And Trends written by Hassanien, Aboul Ella and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-04-03 with Computers categories.


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.



Deep Learning Innovations And Their Convergence With Big Data


Deep Learning Innovations And Their Convergence With Big Data
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Author : Karthik, S.
language : en
Publisher: IGI Global
Release Date : 2017-07-13

Deep Learning Innovations And Their Convergence With Big Data written by Karthik, S. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-13 with Computers categories.


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.



Handbook Of Research On Emerging Trends And Applications Of Machine Learning


Handbook Of Research On Emerging Trends And Applications Of Machine Learning
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Author : Arun Solanki
language : en
Publisher:
Release Date : 2020

Handbook Of Research On Emerging Trends And Applications Of Machine Learning written by Arun Solanki and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Data mining categories.


"This book examines the role of machine learning in various applications such as data mining, natural language processing, image recognition, and expert systems"--.



Optimized Genetic Programming Applications Emerging Research And Opportunities


Optimized Genetic Programming Applications Emerging Research And Opportunities
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Author : Hrnjica, Bahrudin
language : en
Publisher: IGI Global
Release Date : 2018-07-06

Optimized Genetic Programming Applications Emerging Research And Opportunities written by Hrnjica, Bahrudin and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-06 with Medical categories.


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.



Implementation Of Machine Learning Algorithms Using Control Flow And Dataflow Paradigms


Implementation Of Machine Learning Algorithms Using Control Flow And Dataflow Paradigms
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Author : Milutinovi?, Veljko
language : en
Publisher: IGI Global
Release Date : 2022-03-11

Implementation Of Machine Learning Algorithms Using Control Flow And Dataflow Paradigms written by Milutinovi?, Veljko and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-11 with Computers categories.


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.



Trends In Deep Learning Methodologies


Trends In Deep Learning Methodologies
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Author : Vincenzo Piuri
language : en
Publisher: Academic Press
Release Date : 2020-11-12

Trends In Deep Learning Methodologies written by Vincenzo Piuri and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-12 with Computers categories.


Trends in Deep Learning Methodologies: Algorithms, Applications, and Systems covers deep learning approaches such as neural networks, deep belief networks, recurrent neural networks, convolutional neural networks, deep auto-encoder, and deep generative networks, which have emerged as powerful computational models. Chapters elaborate on these models which have shown significant success in dealing with massive data for a large number of applications, given their capacity to extract complex hidden features and learn efficient representation in unsupervised settings. Chapters investigate deep learning-based algorithms in a variety of application, including biomedical and health informatics, computer vision, image processing, and more. In recent years, many powerful algorithms have been developed for matching patterns in data and making predictions about future events. The major advantage of deep learning is to process big data analytics for better analysis and self-adaptive algorithms to handle more data. Deep learning methods can deal with multiple levels of representation in which the system learns to abstract higher level representations of raw data. Earlier, it was a common requirement to have a domain expert to develop a specific model for each specific application, however, recent advancements in representation learning algorithms allow researchers across various subject domains to automatically learn the patterns and representation of the given data for the development of specific models. Provides insights into the theory, algorithms, implementation and the application of deep learning techniques Covers a wide range of applications of deep learning across smart healthcare and smart engineering Investigates the development of new models and how they can be exploited to find appropriate solutions