Описание: Due to the growing use of web applications and communication devices, the use of data has increased throughout various industries. It is necessary to develop new techniques for managing data in order to ensure adequate usage. Deep learning, a subset of artificial intelligence and machine learning, has been recognized in various real-world applications such as computer vision, image processing, and pattern recognition. The deep learning approach has opened new opportunities that can make such real-life applications and tasks easier and more efficient. Deep Learning and Neural Networks: Concepts, Methodologies, Tools, and Applications is a vital reference source that trends in data analytics and potential technologies that will facilitate insight in various domains of science, industry, business, and consumer applications. It also explores the latest concepts, algorithms, and techniques of deep learning and data mining and analysis. Highlighting a range of topics such as natural language processing, predictive analytics, and deep neural networks, this multi-volume book is ideally designed for computer engineers, software developers, IT professionals, academicians, researchers, and upper-level students seeking current research on the latest trends in the field of deep learning.
Автор: Carlo Batini; Monica Scannapieco Название: Data Quality ISBN: 3642069703 ISBN-13(EAN): 9783642069703 Издательство: Springer Рейтинг: Цена: 12577.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Poor data quality can seriously hinder the effectiveness of organizations and businesses. This book offers state of the art understanding of the issues surrounding data quality, and sound practical advice for analyzing and improving data quality in the real world.
Название: Data science for economics and finance ISBN: 3030668932 ISBN-13(EAN): 9783030668938 Издательство: Springer Рейтинг: Цена: 5589.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
This open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for applications in economics and finance. In addition, it shows some successful applications of advanced data science solutions used to extract new knowledge from data in order to improve economic forecasting models.
The book starts with an introduction on the use of data science technologies in economics and finance and is followed by thirteen chapters showing success stories of the application of specific data science methodologies, touching on particular topics related to novel big data sources and technologies for economic analysis (e.g. social media and news); big data models leveraging on supervised/unsupervised (deep) machine learning; natural language processing to build economic and financial indicators; and forecasting and nowcasting of economic variables through time series analysis.
This book is relevant to all stakeholders involved in digital and data-intensive research in economics and finance, helping them to understand the main opportunities and challenges, become familiar with the latest methodological findings, and learn how to use and evaluate the performances of novel tools and frameworks. It primarily targets data scientists and business analysts exploiting data science technologies, and it will also be a useful resource to research students in disciplines and courses related to these topics. Overall, readers will learn modern and effective data science solutions to create tangible innovations for economic and financial applications.
Описание: Further, the book shows how to design and perform a forensic survey, and offers guidance on selecting the best method for the problem at hand, and on selecting the best type of data acquisition and processing.
Описание: How might one determine if a financial institution is taking risk in a balanced and productive manner? It then broadens its gaze to examine various critical applications and extensions of economic capital;
Автор: Lei Meng; Ah-Hwee Tan; Donald C. Wunsch II Название: Adaptive Resonance Theory in Social Media Data Clustering ISBN: 3030029840 ISBN-13(EAN): 9783030029845 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Social media data contains our communication and online sharing, mirroring our daily life. This book looks at how we can use and what we can discover from such big data:Basic knowledge (data & challenges) on social media analyticsClustering as a fundamental technique for unsupervised knowledge discovery and data miningA class of neural inspired algorithms, based on adaptive resonance theory (ART), tackling challenges in big social media data clustering Step-by-step practices of developing unsupervised machine learning algorithms for real-world applications in social media domainAdaptive Resonance Theory in Social Media Data Clustering stands on the fundamental breakthrough in cognitive and neural theory, i.e. adaptive resonance theory, which simulates how a brain processes information to perform memory, learning, recognition, and prediction.It presents initiatives on the mathematical demonstration of ART’s learning mechanisms in clustering, and illustrates how to extend the base ART model to handle the complexity and characteristics of social media data and perform associative analytical tasks.Both cutting-edge research and real-world practices on machine learning and social media analytics are included in the book and if you wish to learn the answers to the following questions, this book is for you:How to process big streams of multimedia data?How to analyze social networks with heterogeneous data?How to understand a user’s interests by learning from online posts and behaviors?How to create a personalized search engine by automatically indexing and searching multimodal information resources? .
Автор: Sergio Consoli; Diego Reforgiato Recupero; Milan P Название: Data Science for Healthcare ISBN: 3030052486 ISBN-13(EAN): 9783030052485 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
This book seeks to promote the exploitation of data science in healthcare systems. The focus is on advancing the automated analytical methods used to extract new knowledge from data for healthcare applications. To do so, the book draws on several interrelated disciplines, including machine learning, big data analytics, statistics, pattern recognition, computer vision, and Semantic Web technologies, and focuses on their direct application to healthcare.
Building on three tutorial-like chapters on data science in healthcare, the following eleven chapters highlight success stories on the application of data science in healthcare, where data science and artificial intelligence technologies have proven to be very promising.
This book is primarily intended for data scientists involved in the healthcare or medical sector. By reading this book, they will gain essential insights into the modern data science technologies needed to advance innovation for both healthcare businesses and patients. A basic grasp of data science is recommended in order to fully benefit from this book.
Описание: This illuminating text/reference surveys the state of the art in data science, and provides practical guidance on big data analytics. presents techniques for machine learning for big data, and identifying duplicate records in data repositories;
Автор: Ahmed S. Ejaz Название: Big and Complex Data Analysis: Methodologies and Applications ISBN: 3319823876 ISBN-13(EAN): 9783319823874 Издательство: Springer Рейтинг: Цена: 12577.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume conveys some of the surprises, puzzles and success stories in high-dimensional and complex data analysis and related fields. Examples include epigenomic data, genomic data, proteomic data, high-resolution image data, high-frequency financial data, functional and longitudinal data, and network data.
Автор: Iv?n Palomares Carrascosa; Harsha Kumara Kalutarag Название: Data Analytics and Decision Support for Cybersecurity ISBN: 3319866249 ISBN-13(EAN): 9783319866246 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Поставка под заказ.
Автор: Management Association Information Reso Название: Big Data: Concepts, Methodologies, Tools, and Applications, VOL 3 ISBN: 1668428016 ISBN-13(EAN): 9781668428016 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 90288.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Management Association Information Reso Название: Big Data: Concepts, Methodologies, Tools, and Applications, VOL 2 ISBN: 1668428008 ISBN-13(EAN): 9781668428009 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 90288.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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