Recent Trends In Learning From Data

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Recent Trends In Learning From Data

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Author : Luca Oneto
language : en
Publisher: Springer Nature
Release Date : 2020-04-03

Recent Trends In Learning From Data written by Luca Oneto and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-03 with Technology & Engineering categories.

This book offers a timely snapshot and extensive practical and theoretical insights into the topic of learning from data. Based on the tutorials presented at the INNS Big Data and Deep Learning Conference, INNSBDDL2019, held on April 16-18, 2019, in Sestri Levante, Italy, the respective chapters cover advanced neural networks, deep architectures, and supervised and reinforcement machine learning models. They describe important theoretical concepts, presenting in detail all the necessary mathematical formalizations, and offer essential guidance on their use in current big data research.

Recent Trends And Future Challenges In Learning From Data

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Author : Cristina Davino
language : en
Publisher: Springer Nature
Release Date : 2024-08-08

Recent Trends And Future Challenges In Learning From Data written by Cristina Davino and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-08 with Computers categories.

This book collects together selected peer-reviewed contributions presented at the European Conference on Data Analysis, ECDA 2022, held in Naples, Italy, September 14-16, 2022. Highlighting the role of statistics in discovering novel and interesting patterns in the era of big data, it follows the motto of the conference: “Avoiding drowning in the data: recent trends and future challenges in learning from data”. The central focus is on multidisciplinary approaches to data analysis, classification, and the interface between computer science, data mining and statistics. Both methodological and applied topics are covered. The former includes supervised and unsupervised techniques with particular emphasis on advances in regression and clustering analysis and constructing composite indicators. The applications are mainly in risk analysis, biology, and education. The volume is organized into four main macro themes: methodological contributions in the social sciences and education, multivariate analysis methods for big data, innovative contributions for applications inspired by biology, and strategies for analyzing complex data in finance.

Recent Trends In Learning From Data

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Author : Luca Oneto
language : en
Publisher: Springer
Release Date : 2021-04-04

Recent Trends In Learning From Data written by Luca Oneto and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-04 with Technology & Engineering categories.

This book offers a timely snapshot and extensive practical and theoretical insights into the topic of learning from data. Based on the tutorials presented at the INNS Big Data and Deep Learning Conference, INNSBDDL2019, held on April 16-18, 2019, in Sestri Levante, Italy, the respective chapters cover advanced neural networks, deep architectures, and supervised and reinforcement machine learning models. They describe important theoretical concepts, presenting in detail all the necessary mathematical formalizations, and offer essential guidance on their use in current big data research.

Learning From Data

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Author : Vladimir Cherkassky
language : en
Publisher: John Wiley & Sons
Release Date : 2007-09-10

Learning From Data written by Vladimir Cherkassky 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 2007-09-10 with Computers categories.

An interdisciplinary framework for learning methodologies—covering statistics, neural networks, and fuzzy logic, this book provides a unified treatment of the principles and methods for learning dependencies from data. It establishes a general conceptual framework in which various learning methods from statistics, neural networks, and fuzzy logic can be applied—showing that a few fundamental principles underlie most new methods being proposed today in statistics, engineering, and computer science. Complete with over one hundred illustrations, case studies, and examples making this an invaluable text.

Learning From Data

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Author : Yaser S. Abu-Mostafa
language : en
Publisher:
Release Date : 2012-01-01

Learning From Data written by Yaser S. Abu-Mostafa and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-01-01 with Machine learning categories.

Trends Of Data Science And Applications

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Author : Siddharth Swarup Rautaray
language : en
Publisher: Springer Nature
Release Date : 2021-03-21

Trends Of Data Science And Applications written by Siddharth Swarup Rautaray and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-21 with Computers categories.

This book includes an extended version of selected papers presented at the 11th Industry Symposium 2021 held during January 7–10, 2021. The book covers contributions ranging from theoretical and foundation research, platforms, methods, applications, and tools in all areas. It provides theory and practices in the area of data science, which add a social, geographical, and temporal dimension to data science research. It also includes application-oriented papers that prepare and use data in discovery research. This book contains chapters from academia as well as practitioners on big data technologies, artificial intelligence, machine learning, deep learning, data representation and visualization, business analytics, healthcare analytics, bioinformatics, etc. This book is helpful for the students, practitioners, researchers as well as industry professional.

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

Learning From Data Streams In Evolving Environments

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Author : Moamar Sayed-Mouchaweh
language : en
Publisher: Springer
Release Date : 2018-07-28

Learning From Data Streams In Evolving Environments written by Moamar Sayed-Mouchaweh and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-28 with Technology & Engineering categories.

This edited book covers recent advances of techniques, methods and tools treating the problem of learning from data streams generated by evolving non-stationary processes. The goal is to discuss and overview the advanced techniques, methods and tools that are dedicated to manage, exploit and interpret data streams in non-stationary environments. The book includes the required notions, definitions, and background to understand the problem of learning from data streams in non-stationary environments and synthesizes the state-of-the-art in the domain, discussing advanced aspects and concepts and presenting open problems and future challenges in this field. Provides multiple examples to facilitate the understanding data streams in non-stationary environments; Presents several application cases to show how the methods solve different real world problems; Discusses the links between methods to help stimulate new research and application directions.

Recent Trends In Computer Aided Diagnostic Systems For Skin Diseases

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Author : Saptarshi Chatterjee
language : en
Publisher: Academic Press
Release Date : 2021-11-07

Recent Trends In Computer Aided Diagnostic Systems For Skin Diseases written by Saptarshi Chatterjee and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-07 with Computers categories.

Recent Trends in Computer-aided Diagnostic Systems for Skin Diseases: Theory, Implementation, and Analysis provides comprehensive coverage on the development of computer-aided diagnostic (CAD) systems employing image processing and machine learning tools for improved, uniform evaluation and diagnosis (avoiding subjective judgment) of skin disorders. The methods and tools are described in a general way so that these tools can be applied not only for skin diseases but also for a wide range of analogous problems in the domain of biomedical systems. Moreover, quantification of clinically relevant information that can associate the findings of physicians/experts is the most challenging task of any CAD system. This book gives all the details in a step-by-step form for different modules so that the readers can develop each of the modules like preprocessing, feature extraction/learning, disease classification, as well as an entire expert diagnosis system themselves for their own applications. - Demonstrates extensive calculations for illustrating the theoretical analysis of advanced image processing and machine learning techniques - Provides a comprehensive coverage on the development of various signal processing tools for the extraction of statistical and clinically correlated features from skin lesion images - Describes image processing and machine learning techniques for improved uniform evaluation and diagnosis of skin disorders

Inference And Learning From Data

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Author : Ali H. Sayed
language : en
Publisher: Cambridge University Press
Release Date : 2022-12-22

Inference And Learning From Data written by Ali H. Sayed and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-22 with Computers categories.

Discover data-driven learning methods with the third volume of this extraordinary three-volume set.