Intelligence Science And Big Data Engineering Big Data And Machine Learning
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Intelligence Science And Big Data Engineering Big Data And Machine Learning Techniques
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Author : Xiaofei He
language : en
Publisher: Springer
Release Date : 2015-10-13
Intelligence Science And Big Data Engineering Big Data And Machine Learning Techniques written by Xiaofei He and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-10-13 with Computers categories.
The two-volume set LNCS 9242 + 9243 constitutes the proceedings of the 5th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2015, held in Suzhou, China, in June 2015. The total of 126 papers presented in the proceedings was carefully reviewed and selected from 416 submissions. They deal with big data, neural networks, image processing, computer vision, pattern recognition and graphics, object detection, dimensionality reduction and manifold learning, unsupervised learning and clustering, anomaly detection, semi-supervised learning.
Machine Learning And Big Data Analytics Paradigms Analysis Applications And Challenges
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Author : Aboul Ella Hassanien
language : en
Publisher: Springer Nature
Release Date : 2020-12-14
Machine Learning And Big Data Analytics Paradigms Analysis Applications And Challenges written by Aboul Ella Hassanien and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-14 with Computers categories.
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.
Intelligence Science And Big Data Engineering Big Data And Machine Learning
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Author : Zhen Cui
language : en
Publisher: Springer Nature
Release Date : 2019-11-28
Intelligence Science And Big Data Engineering Big Data And Machine Learning written by Zhen Cui and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-28 with Computers categories.
The two volumes LNCS 11935 and 11936 constitute the proceedings of the 9th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2019, held in Nanjing, China, in October 2019. The 84 full papers presented were carefully reviewed and selected from 252 submissions.The papers are organized in two parts: visual data engineering; and big data and machine learning. They cover a large range of topics including information theoretic and Bayesian approaches, probabilistic graphical models, big data analysis, neural networks and neuro-informatics, bioinformatics, computational biology and brain-computer interfaces, as well as advances in fundamental pattern recognition techniques relevant to image processing, computer vision and machine learning.
Intelligence Science And Big Data Engineering
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Author : Yuxin Peng
language : en
Publisher: Springer
Release Date : 2018-11-08
Intelligence Science And Big Data Engineering written by Yuxin Peng and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-08 with Computers categories.
This book constitutes the proceedings of the 8th International Conference on Intelligence Science and Big DataEngineering, IScIDE 2018, held in Lanzhou, China, in August 2018.The 59 full papers presented in this book were carefully reviewed and selected from 121 submissions.They are grouped in topical sections on robots and intelligent systems; statistics and learning; deep learning; objects and language; classification and clustering; imaging; and biomedical signal processing.
Blockchain Big Data And Machine Learning
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Author : Neeraj Kumar
language : en
Publisher: CRC Press
Release Date : 2020-09-24
Blockchain Big Data And Machine Learning written by Neeraj Kumar and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-24 with Computers categories.
Present book covers new paradigms in Blockchain, Big Data and Machine Learning concepts including applications and case studies. It explains dead fusion in realizing the privacy and security of blockchain based data analytic environment. Recent research of security based on big data, blockchain and machine learning has been explained through actual work by practitioners and researchers, including their technical evaluation and comparison with existing technologies. The theoretical background and experimental case studies related to real-time environment are covered as well. Aimed at Senior undergraduate students, researchers and professionals in computer science and engineering and electrical engineering, this book: Converges Blockchain, Big Data and Machine learning in one volume. Connects Blockchain technologies with the data centric applications such Big data and E-Health. Easy to understand examples on how to create your own blockchain supported by case studies of blockchain in different industries. Covers big data analytics examples using R. Includes lllustrative examples in python for blockchain creation.
Ai And Big Data S Potential For Disruptive Innovation
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Author : Strydom, Moses
language : en
Publisher: IGI Global
Release Date : 2019-09-27
Ai And Big Data S Potential For Disruptive Innovation written by Strydom, Moses and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-27 with Computers categories.
Big data and artificial intelligence (AI) are at the forefront of technological advances that represent a potential transformational mega-trend—a new multipolar and innovative disruption. These technologies, and their associated management paradigm, are already rapidly impacting many industries and occupations, but in some sectors, the change is just beginning. Innovating ahead of emerging technologies is the new imperative for any organization that aspires to succeed in the next decade. Faced with the power of this AI movement, it is imperative to understand the dynamics and new codes required by the disruption and to adapt accordingly. AI and Big Data’s Potential for Disruptive Innovation provides emerging research exploring the theoretical and practical aspects of successfully implementing new and innovative technologies in a variety of sectors including business, transportation, and healthcare. Featuring coverage on a broad range of topics such as semantic mapping, ethics in AI, and big data governance, this book is ideally designed for IT specialists, industry professionals, managers, executives, researchers, scientists, and engineers seeking current research on the production of new and innovative mechanization and its disruptions.
Computational Intelligence And Big Data Analytics
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Author : Ch. Satyanarayana
language : en
Publisher: Springer
Release Date : 2018-09-22
Computational Intelligence And Big Data Analytics written by Ch. Satyanarayana and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-22 with Computers categories.
This book highlights major issues related to big data analysis using computational intelligence techniques, mostly interdisciplinary in nature. It comprises chapters on computational intelligence technologies, such as neural networks and learning algorithms, evolutionary computation, fuzzy systems and other emerging techniques in data science and big data, ranging from methodologies, theory and algorithms for handling big data, to their applications in bioinformatics and related disciplines. The book describes the latest solutions, scientific results and methods in solving intriguing problems in the fields of big data analytics, intelligent agents and computational intelligence. It reflects the state of the art research in the field and novel applications of new processing techniques in computer science. This book is useful to both doctoral students and researchers from computer science and engineering fields and bioinformatics related domains.
Machine Learning And Big Data
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Author : Uma N. Dulhare
language : en
Publisher: John Wiley & Sons
Release Date : 2020-09-01
Machine Learning And Big Data written by Uma N. Dulhare and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-01 with Computers categories.
This book is intended for academic and industrial developers, exploring and developing applications in the area of big data and machine learning, including those that are solving technology requirements, evaluation of methodology advances and algorithm demonstrations. The intent of this book is to provide awareness of algorithms used for machine learning and big data in the academic and professional community. The 17 chapters are divided into 5 sections: Theoretical Fundamentals; Big Data and Pattern Recognition; Machine Learning: Algorithms & Applications; Machine Learning's Next Frontier and Hands-On and Case Study. While it dwells on the foundations of machine learning and big data as a part of analytics, it also focuses on contemporary topics for research and development. In this regard, the book covers machine learning algorithms and their modern applications in developing automated systems. Subjects covered in detail include: Mathematical foundations of machine learning with various examples. An empirical study of supervised learning algorithms like Naïve Bayes, KNN and semi-supervised learning algorithms viz. S3VM, Graph-Based, Multiview. Precise study on unsupervised learning algorithms like GMM, K-mean clustering, Dritchlet process mixture model, X-means and Reinforcement learning algorithm with Q learning, R learning, TD learning, SARSA Learning, and so forth. Hands-on machine leaning open source tools viz. Apache Mahout, H2O. Case studies for readers to analyze the prescribed cases and present their solutions or interpretations with intrusion detection in MANETS using machine learning. Showcase on novel user-cases: Implications of Electronic Governance as well as Pragmatic Study of BD/ML technologies for agriculture, healthcare, social media, industry, banking, insurance and so on.
Privacy And Security Issues In Big Data
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Author : Pradip Kumar Das
language : en
Publisher: Springer Nature
Release Date : 2021-04-23
Privacy And Security Issues In Big Data written by Pradip Kumar Das and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-23 with Computers categories.
This book focuses on privacy and security concerns in big data and differentiates between privacy and security and privacy requirements in big data. It focuses on the results obtained after applying a systematic mapping study and implementation of security in the big data for utilizing in business under the establishment of “Business Intelligence”. The chapters start with the definition of big data, discussions why security is used in business infrastructure and how the security can be improved. In this book, some of the data security and data protection techniques are focused and it presents the challenges and suggestions to meet the requirements of computing, communication and storage capabilities for data mining and analytics applications with large aggregate data in business.
Foundations Of Data Science For Engineering Problem Solving
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Author : Parikshit Narendra Mahalle
language : en
Publisher:
Release Date : 2022
Foundations Of Data Science For Engineering Problem Solving written by Parikshit Narendra Mahalle and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with categories.
This book is one-stop shop which offers essential information one must know and can implement in real-time business expansions to solve engineering problems in various disciplines. It will also help us to make future predictions and decisions using AI algorithms for engineering problems. Machine learning and optimizing techniques provide strong insights into novice users. In the era of big data, there is a need to deal with data science problems in multidisciplinary perspective. In the real world, data comes from various use cases, and there is a need of source specific data science models. Information is drawn from various platforms, channels, and sectors including web-based media, online business locales, medical services studies, and Internet. To understand the trends in the market, data science can take us through various scenarios. It takes help of artificial intelligence and machine learning techniques to design and optimize the algorithms. Big data modelling and visualization techniques of collected data play a vital role in the field of data science. This book targets the researchers from areas of artificial intelligence, machine learning, data science and big data analytics to look for new techniques in business analytics and applications of artificial intelligence in recent businesses.