Bayesian Optimization And Data Science
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Bayesian Optimization And Data Science
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Author : Francesco Archetti
language : en
Publisher: Springer Nature
Release Date : 2019-09-25
Bayesian Optimization And Data Science written by Francesco Archetti and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-25 with Business & Economics categories.
This volume brings together the main results in the field of Bayesian Optimization (BO), focusing on the last ten years and showing how, on the basic framework, new methods have been specialized to solve emerging problems from machine learning, artificial intelligence, and system optimization. It also analyzes the software resources available for BO and a few selected application areas. Some areas for which new results are shown include constrained optimization, safe optimization, and applied mathematics, specifically BO's use in solving difficult nonlinear mixed integer problems. The book will help bring readers to a full understanding of the basic Bayesian Optimization framework and gain an appreciation of its potential for emerging application areas. It will be of particular interest to the data science, computer science, optimization, and engineering communities.
Bayesian Approach To Global Optimization
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Author : Jonas Mockus
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Bayesian Approach To Global Optimization written by Jonas Mockus and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Mathematics categories.
·Et moi ... si j'avait su comment en revcnir. One service mathematics has rendered the je o'y semis point alle.' human race. It has put common sense back Jules Verne where it beloogs. on the topmost shelf next to the dusty canister labelled 'discarded non The series is divergent; therefore we may be sense', able to do something with it. Eric T. BclI O. Heaviside Mathematics is a tool for thought. A highly necessary tool in a world where both feedback and non linearities abound. Similarly, all kinds of parts of mathematics serve as tools for other parts and for other sciences. Applying a simple rewriting rule to the quote on the right above one finds such statements as: 'One service topology has rendered mathematical physics ... '; 'One service logic has rendered com puter science .. .'; 'One service category theory has rendered mathematics .. .'. All arguably true. And all statements obtainable this way form part of the raison d'etre of this series.
Machine Learning Optimization And Data Science
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Author : Giuseppe Nicosia
language : en
Publisher: Springer Nature
Release Date : 2021-01-06
Machine Learning Optimization And Data Science written by Giuseppe Nicosia and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-06 with Computers categories.
This two-volume set, LNCS 12565 and 12566, constitutes the refereed proceedings of the 6th International Conference on Machine Learning, Optimization, and Data Science, LOD 2020, held in Siena, Italy, in July 2020. The total of 116 full papers presented in this two-volume post-conference proceedings set was carefully reviewed and selected from 209 submissions. These research articles were written by leading scientists in the fields of machine learning, artificial intelligence, reinforcement learning, computational optimization, and data science presenting a substantial array of ideas, technologies, algorithms, methods, and applications.
Data Science Analytics And Applications
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Author : Peter Haber
language : en
Publisher: Springer Nature
Release Date : 2022-03-29
Data Science Analytics And Applications written by Peter Haber and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-29 with Computers categories.
Organizations have moved already from the rigid structure of classical project management towards the adoption of agile approaches. This holds also true for software development projects, which need to be flexible to adopt to rapid requests of clients as well to reflect changes that are required due to architectural design decisions. With data science having established itself as corner stone within organizations and businesses, it is now imperative to perform this crucial step for analytical business processes as well. The non-deterministic nature of data science and its inherent analytical tasks require an interactive approach towards an evolutionary step-by-step development to realize core essential business applications and use cases. The 4th International Data Science Conference (iDSC) 2021 brought together researchers, scientists, and business experts to discuss means of establishing new ways of embracing agile approaches within the various domains of data science, such as machine learning and AI, data mining, or visualization and communication as well as case studies and best practices from leading research institutions and business companies. The proceedings include all full papers presented in the scientific track and the corresponding German abstracts as well as the short papers from the student track. Among the topics of interest are: Artificial Intelligence and Machine Learning Implementation of data mining processes Agile Data Science and Visualization Case Studies and Applications for Agile Data Science --- Organisationen sind bereits von der starren Struktur des klassischen Projektmanagements zu agilen Ansätzen übergegangen. Dies gilt auch für Softwareentwicklungsprojekte, die flexibel sein müssen, um schnell auf die Wünsche der Kunden reagieren zu können und um Änderungen zu berücksichtigen, die aufgrund von Architekturentscheidungen erforderlich sind. Nachdem sich die Datenwissenschaft als Eckpfeiler in Organisationen und Unternehmen etabliert hat, ist es nun zwingend erforderlich, diesen entscheidenden Schritt auch für analytische Geschäftsprozesse durchzuführen. Die nicht-deterministische Natur der Datenwissenschaft und die ihr innewohnenden analytischen Aufgaben erfordern einen interaktiven Ansatz für eine evolutionäre, schrittweise Entwicklung zur Realisierung der wichtigsten Geschäftsanwendungen und Anwendungsfälle. Die 4. Internationale Konferenz zur Datenwissenschaft (iDSC 2021) brachte Forscher, Wissenschaftler und Wirtschaftsexperten zusammen, um Möglichkeiten zu erörtern, wie neue Wege zur Umsetzung agiler Ansätze in den verschiedenen Bereichen der Datenwissenschaft, wie maschinelles Lernen und KI, Data Mining oder Visualisierung und Kommunikation, sowie Fallstudien und Best Practices von führenden Forschungseinrichtungen und Wirtschaftsunternehmen etabliert werden können. Der Tagungsband umfasst alle im wissenschaftlichen Track vorgestellten Volltexte und die Kurzbeiträge aus dem studentischen Track auf Englisch und die dazugehörigen Abstracts auf Deutsch. Zu den Themen, die sie interessieren, gehören unter anderem: Künstliche Intelligenz und Maschinelles Lernen Implementierung von Data-Mining-Prozessen Agile Datenwissenschaft und Visualisierung Fallstudien und Anwendungen für Agile Datenwissenschaft
Advanced Methods In Statistics Data Science And Related Applications
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Author : Matilde Bini
language : en
Publisher: Springer Nature
Release Date : 2024-10-16
Advanced Methods In Statistics Data Science And Related Applications written by Matilde Bini and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-16 with Computers categories.
This book contains a selection of the improved contributions submitted by participants at the conference of the Italian Statistical Society - SIS 2022 held in Caserta 22-24 June 2022. The scientific community of Italian statistics, which gathers around the SIS, is paying particular attention to the development of statistical techniques increasingly oriented toward the processing of large data, mainly, of complex data. The main goal is to provide the analysis of the data and the interpretability of the obtained results, with a view to decision support and the reliability of the data outcomes. The aim of this volume is to show some of the most relevant contributions of statistical and data analysis methods in preserving the quality of the information to be processed, especially when it comes from different, often non-official sources; as well as in the extraction of knowledge from complex data (textual, network, unstructured and multivalue) and in the explicability of results. Data Science today represents a broad domain of knowledge development from data, where statistical and data analysis methods can make an important contribution in the different domains where data management and processing are required. This volume is addressed to researchers but also to Ph.D. and MSc students in the field of Statistics and Data Science to acquaint them with some of the most recent developments towards which statistical research is orienting, in prevalence in Italy.
Data Analysis
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Author : Devinderjit Sivia
language : en
Publisher: OUP Oxford
Release Date : 2006-06-02
Data Analysis written by Devinderjit Sivia and has been published by OUP Oxford this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-06-02 with Mathematics categories.
One of the strengths of this book is the author's ability to motivate the use of Bayesian methods through simple yet effective examples. - Katie St. Clair MAA Reviews.
Practical Statistical Learning And Data Science Methods
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Author : O. Olawale Awe
language : en
Publisher: Springer Nature
Release Date : 2024-12-27
Practical Statistical Learning And Data Science Methods written by O. Olawale Awe and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-27 with Computers categories.
This contributed volume offers practical implementation strategies for statistical learning and data science techniques, with fully peer-reviewed papers that embody insights and experiences gathered within the LISA 2020 Global Network. Through a series of compelling case studies, readers are immersed in practical methodologies, real-world applications, and innovative approaches in statistical learning and data science. Topics covered in this volume span a wide array of applications, including machine learning in health data analysis, deep learning models for precipitation modeling, interpretation techniques for machine learning models in BMI classification for obesity studies, as well as a comparative analysis of sampling methods in machine learning health applications. By addressing the evolving landscape of data analytics in many ways, this volume serves as a valuable resource for practitioners, researchers, and students alike. The LISA 2020 Global Network is dedicated to enhancing statistical and data science capabilities in developing countries through the establishment of collaboration laboratories, also known as “stat labs.” These stat labs function as engines for development, nurturing the next generation of collaborative statisticians and data scientists while providing essential research infrastructure for researchers, data producers, and decision-makers.
Data Science In Theory And Practice
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Author : Jaydip Sen
language : en
Publisher: Cambridge Scholars Publishing
Release Date : 2024-09-13
Data Science In Theory And Practice written by Jaydip Sen and has been published by Cambridge Scholars Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-13 with Data integrity categories.
This comprehensive edited volume showcases the latest breakthroughs and innovative research in the rapidly evolving field of data science, and brings together contributions from leading experts and researchers who push the boundaries of the field, offering readers a deep insight into the diverse facets of this transformative discipline. Spanning a wide spectrum of topics, the chapters in this volume cover key areas such as machine learning, artificial intelligence, statistical analysis, and ethical considerations in data science. Each chapter is a testament to the ongoing quest for knowledge and the relentless pursuit of excellence in harnessing the power of data for meaningful insights and actionable intelligence. Whether you're an experienced data scientist, a researcher exploring the frontiers of the field, or a novice eager to grasp the fundamentals, this edited volume serves as a valuable resource. The compilation not only highlights the current state of data science but also anticipates future trends, paving the way for continued advancements and paradigm shifts in the way we approach, analyze, and leverage data.
Bayesian Data Analysis Third Edition
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Author : Andrew Gelman
language : en
Publisher: CRC Press
Release Date : 2013-11-01
Bayesian Data Analysis Third Edition written by Andrew Gelman and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-01 with Mathematics categories.
Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors—all leaders in the statistics community—introduce basic concepts from a data-analytic perspective before presenting advanced methods. Throughout the text, numerous worked examples drawn from real applications and research emphasize the use of Bayesian inference in practice. New to the Third Edition Four new chapters on nonparametric modeling Coverage of weakly informative priors and boundary-avoiding priors Updated discussion of cross-validation and predictive information criteria Improved convergence monitoring and effective sample size calculations for iterative simulation Presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation New and revised software code The book can be used in three different ways. For undergraduate students, it introduces Bayesian inference starting from first principles. For graduate students, the text presents effective current approaches to Bayesian modeling and computation in statistics and related fields. For researchers, it provides an assortment of Bayesian methods in applied statistics. Additional materials, including data sets used in the examples, solutions to selected exercises, and software instructions, are available on the book’s web page.
Bayesian Process Monitoring Control And Optimization
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Author : Bianca M. Colosimo
language : en
Publisher: CRC Press
Release Date : 2006-11-10
Bayesian Process Monitoring Control And Optimization written by Bianca M. Colosimo and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-11-10 with Business & Economics categories.
Although there are many Bayesian statistical books that focus on biostatistics and economics, there are few that address the problems faced by engineers. Bayesian Process Monitoring, Control and Optimization resolves this need, showing you how to oversee, adjust, and optimize industrial processes. Bridging the gap between application and dev