AI and Big Data`s Potential for Disruptive Innovation, Moses Strydom, Sheryl Buckley
Автор: Moses Strydom, Sheryl Buckley Название: AI and Big Data`s Potential for Disruptive Innovation ISBN: 1522596879 ISBN-13(EAN): 9781522596875 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 30215.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 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.
Автор: Neha Sharma; Amlan Chakrabarti; Valentina Emilia B Название: Data Management, Analytics and Innovation ISBN: 981139363X ISBN-13(EAN): 9789811393631 Издательство: Springer Рейтинг: Цена: 23757.00 р. Наличие на складе: Поставка под заказ.
Описание: This book presents the latest findings in the areas of data management and smart computing, big data management, artificial intelligence and data analytics, along with advances in network technologies. It addresses state-of-the-art topics and discusses challenges and solutions for future development. Gathering original, unpublished contributions by scientists from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia and industry.
Автор: Zaitsev A.M. Название: Optical Properties of Diamond / A Data Handbook ISBN: 354066582X ISBN-13(EAN): 9783540665823 Издательство: Springer Рейтинг: Цена: 39130.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This handbook is the most comprehensive compilation of data on the optical properties of diamond ever written. It presents a multitude of data previously for the first time in English. The author provides quick access to the most comprehensive information on all aspects of the field.
Автор: Hsu, Hui-Huang Название: Big Data Analytics for Sensor-Network Collected Intelligence ISBN: 0128093935 ISBN-13(EAN): 9780128093931 Издательство: Elsevier Science Рейтинг: Цена: 15159.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Big Data Analytics for Sensor-Network Collected Intelligence explores state-of-the-art methods for using advanced ICT technologies to perform intelligent analysis on sensor collected data. The book shows how to develop systems that automatically detect natural and human-made events, how to examine people's behaviors, and how to unobtrusively provide better services.
It begins by exploring big data architecture and platforms, covering the cloud computing infrastructure and how data is stored and visualized. The book then explores how big data is processed and managed, the key security and privacy issues involved, and the approaches used to ensure data quality.
In addition, readers will find a thorough examination of big data analytics, analyzing statistical methods for data analytics and data mining, along with a detailed look at big data intelligence, ubiquitous and mobile computing, and designing intelligence system based on context and situation.
Indexing: The books of this series are submitted to EI-Compendex and SCOPUS
Contains contributions from noted scholars in computer science and electrical engineering from around the globe
Provides a broad overview of recent developments in sensor collected intelligence
Edited by a team comprised of leading thinkers in big data analytics
Описание: The book starts with the quote of the classical Pearson definition of PCA and includes reviews of various methods: NLPCA, ICA, MDS, embedding and clustering algorithms, principal manifolds and SOM. New approaches to NLPCA, principal manifolds, branching principal components and topology preserving mappings are described.
Автор: Clarke Название: Principles and Theory for Data Mining and Machine Learning ISBN: 0387981349 ISBN-13(EAN): 9780387981345 Издательство: Springer Рейтинг: Цена: 27950.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Extensive treatment of the most up-to-date topicsProvides the theory and concepts behind popular and emerging methodsRange of topics drawn from Statistics, Computer Science, and Electrical Engineering
Описание: This book explores and analyzes emerging innovations within today`s most cutting-edge science and technology (S&T) areas, which are cited as carrying the potential to revolutionize governmental structures, economies, and international security.
Автор: Pablo Duboue Название: The Art of Feature Engineering: Essentials for Machine Learning ISBN: 1108709389 ISBN-13(EAN): 9781108709385 Издательство: Cambridge Academ Рейтинг: Цена: 6970.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This is a guide for data scientists who want to use feature engineering to improve the performance of their machine learning solutions. The book provides a unified view of the field, beginning with basic concepts and techniques, followed by a cross-domain approach to advanced topics, like texts and images, with hands-on case studies.
Описание: This proceeding features papers discussing big data innovation for sustainable cognitive computing. The papers feature detail on cognitive computing and its self-learning systems that use data mining, pattern recognition and natural language processing (NLP) to mirror the way the human brain works. This international conference focuses on cognitive computing technologies, from knowledge representation techniques and natural language processing algorithms to dynamic learning approaches. Topics covered include Data Science for Cognitive Analysis, Real-Time Ubiquitous Data Science, Platform for Privacy Preserving Data Science, and Internet-Based Cognitive Platform. The EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing (BDCC 2018), took place on 13 – 15 December 2018 in Coimbatore, India.
Автор: Balas Название: Data Management, Analytics and Innovation ISBN: 9811312737 ISBN-13(EAN): 9789811312731 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The volume on Data Management, Analytics and Innovations presents the latest high-quality technical contributions and research results in the areas of data management and smart computing, big data management, artificial intelligence and data analytics along with advances in network technologies.
Автор: Shalin Hai-Jew Название: Social Media Data Extraction and Content Analysis ISBN: 1522506489 ISBN-13(EAN): 9781522506485 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 33403.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Explores various social networking platforms and the technologies being utilized to gather and analyse information being posted to these venues. Highlighting emergent research, analytical techniques, and best practices in data extraction in global electronic culture, this publication is an essential reference source for researchers, academics, and professionals.
Автор: Li, Fanzhang / Zhang, Li / Zhang, Zhao Название: Dynamic Fuzzy Machine Learning ISBN: 3110518708 ISBN-13(EAN): 9783110518702 Издательство: Walter de Gruyter Рейтинг: Цена: 22439.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Machine learning is widely used for data analysis. Dynamic fuzzy data are one of the most difficult types of data to analyse in the field of big data, cloud computing, the Internet of Things, and quantum information. At present, the processing of this kind of data is not very mature. The authors carried out more than 20 years of research, and show in this book their most important results. The seven chapters of the book are devoted to key topics such as dynamic fuzzy machine learning models, dynamic fuzzy self-learning subspace algorithms, fuzzy decision tree learning, dynamic concepts based on dynamic fuzzy sets, semi-supervised multi-task learning based on dynamic fuzzy data, dynamic fuzzy hierarchy learning, examination of multi-agent learning model based on dynamic fuzzy logic. This book can be used as a reference book for senior college students and graduate students as well as college teachers and scientific and technical personnel involved in computer science, artificial intelligence, machine learning, automation, data analysis, mathematics, management, cognitive science, and finance. It can be also used as the basis for teaching the principles of dynamic fuzzy learning.
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