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Information-Theoretic Methods in Data Science

Information-Theoretic Methods in Data Science PDF Author: Miguel R. D. Rodrigues
Publisher: Cambridge University Press
ISBN: 1108427138
Category : Computers
Languages : en
Pages : 561

Book Description
The first unified treatment of the interface between information theory and emerging topics in data science, written in a clear, tutorial style. Covering topics such as data acquisition, representation, analysis, and communication, it is ideal for graduate students and researchers in information theory, signal processing, and machine learning.

Information-Theoretic Methods in Data Science

Information-Theoretic Methods in Data Science PDF Author: Miguel R. D. Rodrigues
Publisher: Cambridge University Press
ISBN: 1108427138
Category : Computers
Languages : en
Pages : 561

Book Description
The first unified treatment of the interface between information theory and emerging topics in data science, written in a clear, tutorial style. Covering topics such as data acquisition, representation, analysis, and communication, it is ideal for graduate students and researchers in information theory, signal processing, and machine learning.

Information Theory and Statistical Learning

Information Theory and Statistical Learning PDF Author: Frank Emmert-Streib
Publisher: Springer Science & Business Media
ISBN: 0387848150
Category : Computers
Languages : en
Pages : 443

Book Description
This interdisciplinary text offers theoretical and practical results of information theoretic methods used in statistical learning. It presents a comprehensive overview of the many different methods that have been developed in numerous contexts.

Statistical Inference for Engineers and Data Scientists

Statistical Inference for Engineers and Data Scientists PDF Author: Pierre Moulin
Publisher: Cambridge University Press
ISBN: 1107185920
Category : Mathematics
Languages : en
Pages : 423

Book Description
A mathematically accessible textbook introducing all the tools needed to address modern inference problems in engineering and data science.

Information Theory, Inference and Learning Algorithms

Information Theory, Inference and Learning Algorithms PDF Author: David J. C. MacKay
Publisher: Cambridge University Press
ISBN: 9780521642989
Category : Computers
Languages : en
Pages : 694

Book Description
Table of contents

Model Selection and Multimodel Inference

Model Selection and Multimodel Inference PDF Author: Kenneth P. Burnham
Publisher: Springer Science & Business Media
ISBN: 0387224564
Category : Mathematics
Languages : en
Pages : 488

Book Description
A unique and comprehensive text on the philosophy of model-based data analysis and strategy for the analysis of empirical data. The book introduces information theoretic approaches and focuses critical attention on a priori modeling and the selection of a good approximating model that best represents the inference supported by the data. It contains several new approaches to estimating model selection uncertainty and incorporating selection uncertainty into estimates of precision. An array of examples is given to illustrate various technical issues. The text has been written for biologists and statisticians using models for making inferences from empirical data.

Information Theory and Statistics

Information Theory and Statistics PDF Author: Solomon Kullback
Publisher: Courier Corporation
ISBN: 0486142043
Category : Mathematics
Languages : en
Pages : 460

Book Description
Highly useful text studies logarithmic measures of information and their application to testing statistical hypotheses. Includes numerous worked examples and problems. References. Glossary. Appendix. 1968 2nd, revised edition.

Information Theoretic Perspectives on 5G Systems and Beyond

Information Theoretic Perspectives on 5G Systems and Beyond PDF Author: Ivana Marić
Publisher:
ISBN: 1108271367
Category : Language Arts & Disciplines
Languages : en
Pages : 768

Book Description
Understand key information-theoretic principles that underpin the design of next-generation cellular systems with this invaluable resource. This book is the perfect tool for researchers and graduate students in the field of information theory and wireless communications, as well as for practitioners in the telecommunications industry.

Data Science

Data Science PDF Author: Qurban A Memon
Publisher: CRC Press
ISBN: 0429554354
Category : Computers
Languages : en
Pages : 325

Book Description
The aim of this book is to provide an internationally respected collection of scientific research methods, technologies and applications in the area of data science. This book can prove useful to the researchers, professors, research students and practitioners as it reports novel research work on challenging topics in the area surrounding data science. In this book, some of the chapters are written in tutorial style concerning machine learning algorithms, data analysis, information design, infographics, relevant applications, etc. The book is structured as follows: • Part I: Data Science: Theory, Concepts, and Algorithms This part comprises five chapters on data Science theory, concepts, techniques and algorithms. • Part II: Data Design and Analysis This part comprises five chapters on data design and analysis. • Part III: Applications and New Trends in Data Science This part comprises four chapters on applications and new trends in data science.

Information Theory

Information Theory PDF Author: Imre Csiszár
Publisher: Elsevier
ISBN: 1483281574
Category : Mathematics
Languages : en
Pages : 460

Book Description
Information Theory: Coding Theorems for Discrete Memoryless Systems presents mathematical models that involve independent random variables with finite range. This three-chapter text specifically describes the characteristic phenomena of information theory. Chapter 1 deals with information measures in simple coding problems, with emphasis on some formal properties of Shannon’s information and the non-block source coding. Chapter 2 describes the properties and practical aspects of the two-terminal systems. This chapter also examines the noisy channel coding problem, the computation of channel capacity, and the arbitrarily varying channels. Chapter 3 looks into the theory and practicality of multi-terminal systems. This book is intended primarily for graduate students and research workers in mathematics, electrical engineering, and computer science.

Data Science and Machine Learning

Data Science and Machine Learning PDF Author: Dirk P. Kroese
Publisher: CRC Press
ISBN: 1000730778
Category : Business & Economics
Languages : en
Pages : 538

Book Description
Focuses on mathematical understanding Presentation is self-contained, accessible, and comprehensive Full color throughout Extensive list of exercises and worked-out examples Many concrete algorithms with actual code