Download or read book Mathematical Foundations for Social Analysis written by Robert McGinnis and published by . This book was released on with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Mathematical Foundations for Data Analysis written by Jeff M. Phillips and published by Springer Nature. This book was released on 2021-03-29 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook, suitable for an early undergraduate up to a graduate course, provides an overview of many basic principles and techniques needed for modern data analysis. In particular, this book was designed and written as preparation for students planning to take rigorous Machine Learning and Data Mining courses. It introduces key conceptual tools necessary for data analysis, including concentration of measure and PAC bounds, cross validation, gradient descent, and principal component analysis. It also surveys basic techniques in supervised (regression and classification) and unsupervised learning (dimensionality reduction and clustering) through an accessible, simplified presentation. Students are recommended to have some background in calculus, probability, and linear algebra. Some familiarity with programming and algorithms is useful to understand advanced topics on computational techniques.
Download or read book Mathematical Foundations for Social Analysis written by Robert McGinnis and published by . This book was released on 1965 with total page 450 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Mathematical Foundation for Social Analysis written by and published by . This book was released on 1965 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Essential Mathematics for Political and Social Research written by Jeff Gill and published by Cambridge University Press. This book was released on 2006-04-24 with total page 449 pages. Available in PDF, EPUB and Kindle. Book excerpt: "More than ever before, modern social scientists require a basic level of mathematical literacy, yet many students receive only limited mathematical training prior to beginning their research careers. This textbook addresses this dilemma by offering a comprehensive, unified introduction to the essential mathematics of social science. Throughout the book the presentation builds from first principles and eschews unnecessary complexity. Most importantly, the discussion is thoroughly and consistently anchored in real social science applications, with more than 80 research-based illustrations woven into the text and featured in end-of-chapter exercises. Students and researchers alike will find this first-of-its-kind volume to be an invaluable resource."--BOOK JACKET.
Download or read book Foundations of Mathematical Analysis written by Saminathan Ponnusamy and published by Springer Science & Business Media. This book was released on 2011-12-16 with total page 575 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical analysis is fundamental to the undergraduate curriculum not only because it is the stepping stone for the study of advanced analysis, but also because of its applications to other branches of mathematics, physics, and engineering at both the undergraduate and graduate levels. This self-contained textbook consists of eleven chapters, which are further divided into sections and subsections. Each section includes a careful selection of special topics covered that will serve to illustrate the scope and power of various methods in real analysis. The exposition is developed with thorough explanations, motivating examples, exercises, and illustrations conveying geometric intuition in a pleasant and informal style to help readers grasp difficult concepts. Foundations of Mathematical Analysis is intended for undergraduate students and beginning graduate students interested in a fundamental introduction to the subject. It may be used in the classroom or as a self-study guide without any required prerequisites.
Download or read book Mathematical Foundations of Time Series Analysis written by Jan Beran and published by Springer. This book was released on 2018-03-23 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a concise introduction to the mathematical foundations of time series analysis, with an emphasis on mathematical clarity. The text is reduced to the essential logical core, mostly using the symbolic language of mathematics, thus enabling readers to very quickly grasp the essential reasoning behind time series analysis. It appeals to anybody wanting to understand time series in a precise, mathematical manner. It is suitable for graduate courses in time series analysis but is equally useful as a reference work for students and researchers alike.
Download or read book The Dynamics and Evolution of Social Systems written by Jürgen Klüver and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: When I started with this book several years ago I originally intended to write an introduction to mathematical systems theory for social scientists. Yet the more I thought about systems theory on the one side and theoretical sociology on the other the more I became convinced that the classical mathematical tools are not very well suited for the problems of sociology. Then I became acquainted with the researches on complex systems by the Santa Fe Institute and in particular with cellular automata, Boolean networks and genetic algorithms. These mathematically very simple but extremely efficient tools are, in my opinion, very well appropriate for modeling social dynamics. Therefore I tried to reformulate several classical problems of theoretical sociology in terms of these formal systems and outline new possibilities for a mathematical sociology which is able to join immediately on the great traditions of theoretical sociology. The result is this book; whether I succeeded with it is of course up to the readers. As the readers will perceive, the book could not have been written by me alone but only by the joint labors of the computer group at the Interdisciplinary Center of Research in Higher Education at the University of Essen. The members of the group, Christina Stoica, Jom Schmidt and Ralph Kier, are named in several subchapters as co-authors. Yet even more important than their contributions to this book were the permanent discussions with them and their patience with my new and very speculative ideas. Many thanks.
Download or read book Mathematical Foundations for Signal Processing Communications and Networking written by Erchin Serpedin and published by CRC Press. This book was released on 2017-12-04 with total page 859 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical Foundations for Signal Processing, Communications, and Networking describes mathematical concepts and results important in the design, analysis, and optimization of signal processing algorithms, modern communication systems, and networks. Helping readers master key techniques and comprehend the current research literature, the book offers a comprehensive overview of methods and applications from linear algebra, numerical analysis, statistics, probability, stochastic processes, and optimization. From basic transforms to Monte Carlo simulation to linear programming, the text covers a broad range of mathematical techniques essential to understanding the concepts and results in signal processing, telecommunications, and networking. Along with discussing mathematical theory, each self-contained chapter presents examples that illustrate the use of various mathematical concepts to solve different applications. Each chapter also includes a set of homework exercises and readings for additional study. This text helps readers understand fundamental and advanced results as well as recent research trends in the interrelated fields of signal processing, telecommunications, and networking. It provides all the necessary mathematical background to prepare students for more advanced courses and train specialists working in these areas.
Download or read book Mathematical Foundations of Data Science Using R written by Frank Emmert-Streib and published by Walter de Gruyter GmbH & Co KG. This book was released on 2022-10-24 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of the book is to help students become data scientists. Since this requires a series of courses over a considerable period of time, the book intends to accompany students from the beginning to an advanced understanding of the knowledge and skills that define a modern data scientist. The book presents a comprehensive overview of the mathematical foundations of the programming language R and of its applications to data science.
Download or read book Formal Concept Analysis written by Bernhard Ganter and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: This first textbook on formal concept analysis gives a systematic presentation of the mathematical foundations and their relations to applications in computer science, especially in data analysis and knowledge processing. Above all, it presents graphical methods for representing conceptual systems that have proved themselves in communicating knowledge. The mathematical foundations are treated thoroughly and are illuminated by means of numerous examples, making the basic theory readily accessible in compact form.
Download or read book Mathematical Foundations of Big Data Analytics written by Vladimir Shikhman and published by Springer Nature. This book was released on 2021-02-11 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this textbook, basic mathematical models used in Big Data Analytics are presented and application-oriented references to relevant practical issues are made. Necessary mathematical tools are examined and applied to current problems of data analysis, such as brand loyalty, portfolio selection, credit investigation, quality control, product clustering, asset pricing etc. – mainly in an economic context. In addition, we discuss interdisciplinary applications to biology, linguistics, sociology, electrical engineering, computer science and artificial intelligence. For the models, we make use of a wide range of mathematics – from basic disciplines of numerical linear algebra, statistics and optimization to more specialized game, graph and even complexity theories. By doing so, we cover all relevant techniques commonly used in Big Data Analytics.Each chapter starts with a concrete practical problem whose primary aim is to motivate the study of a particular Big Data Analytics technique. Next, mathematical results follow – including important definitions, auxiliary statements and conclusions arising. Case-studies help to deepen the acquired knowledge by applying it in an interdisciplinary context. Exercises serve to improve understanding of the underlying theory. Complete solutions for exercises can be consulted by the interested reader at the end of the textbook; for some which have to be solved numerically, we provide descriptions of algorithms in Python code as supplementary material.This textbook has been recommended and developed for university courses in Germany, Austria and Switzerland.
Download or read book Introductory Mathematical Analysis for Business Economics and the Life and Social Sciences written by Ernest F. Haeussler and published by Prentice Hall. This book was released on 2005 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introductory Mathematical Analysis continues to provide a mathematical foundation for students in business, economics, and the life and social sciences. The abundant applications in the book cover such diverse areas as business, economics, biology, medicine, sociology, psychology, ecology, statistics, earth science, and archaeology.For anyone interested in learning more about introductory mathematical analysis.
Download or read book Introductory Mathematical Analysis for Business Economics and the Life and Social Sciences Global Edition written by Ernest F Haeussler and published by Pearson Higher Ed. This book was released on 2021-08-10 with total page 853 pages. Available in PDF, EPUB and Kindle. Book excerpt: Thisbook is ideal for one- or two-semester or two- or three-quarter coursescovering topics in college algebra, finite mathematics, and calculus forstudents in business, economics, and the life and social sciences. Introductory Mathematical Analysis forBusiness, Economics, and the Life and Social Sciences provides a mathematical foundation for students in avariety of fields and majors. The authors establish an emphasis on algebraiccalculations that sets this text apart from other introductory, appliedmathematics books. Because the process of calculating variables builds skillsin mathematical modeling, this emphasis paves the way for students to solvereal-world problems that use calculus. The book’s comprehensive structure—covering college algebra in Chapters0 through 4, finite mathematics in Chapters 5 through 9, and calculus inChapters 10 through 17—offers instructors flexibility in how they use thematerial based on the course they’re teaching, the semester they’re at, or whatthe students’ background allows and their needs dictate.
Download or read book Mathematical Foundations of Speech and Language Processing written by Mark Johnson and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: Speech and language technologies continue to grow in importance as they are used to create natural and efficient interfaces between people and machines, and to automatically transcribe, extract, analyze, and route information from high-volume streams of spoken and written information. The workshops on Mathematical Foundations of Speech Processing and Natural Language Modeling were held in the Fall of 2000 at the University of Minnesota's NSF-sponsored Institute for Mathematics and Its Applications, as part of a "Mathematics in Multimedia" year-long program. Each workshop brought together researchers in the respective technologies on the one hand, and mathematicians and statisticians on the other hand, for an intensive week of cross-fertilization. There is a long history of benefit from introducing mathematical techniques and ideas to speech and language technologies. Examples include the source-channel paradigm, hidden Markov models, decision trees, exponential models and formal languages theory. It is likely that new mathematical techniques, or novel applications of existing techniques, will once again prove pivotal for moving the field forward. This volume consists of original contributions presented by participants during the two workshops. Topics include language modeling, prosody, acoustic-phonetic modeling, and statistical methodology.
Download or read book Mathematical Foundations for Computing written by G. P. McKeown and published by Palgrave. This book was released on 1995 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text gives a description of the fundamental mathematical concepts used by computer scientists, while also emphasizing the need for careful justification. It provides proofs of all the major results, and all the algorithms presented are developed carefully and their performance analyzed. Throughout, the aim is to provide a well-balanced treatment of both the discrete and continuous mathematics that should be studied by the serious student of computer science. The book should therefore be most suited to those undergraduate programmes that put the emphasis on such areas as programming language semantics, program correctness, and algorithm analysis and design.
Download or read book General Systems Theory Mathematical Foundations written by and published by Academic Press. This book was released on 1975-03-21 with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, we study theoretical and practical aspects of computing methods for mathematical modelling of nonlinear systems. A number of computing techniques are considered, such as methods of operator approximation with any given accuracy; operator interpolation techniques including a non-Lagrange interpolation; methods of system representation subject to constraints associated with concepts of causality, memory and stationarity; methods of system representation with an accuracy that is the best within a given class of models; methods of covariance matrix estimation;methods for low-rank matrix approximations; hybrid methods based on a combination of iterative procedures and best operator approximation; andmethods for information compression and filtering under condition that a filter model should satisfy restrictions associated with causality and different types of memory.As a result, the book represents a blend of new methods in general computational analysis,and specific, but also generic, techniques for study of systems theory ant its particularbranches, such as optimal filtering and information compression. - Best operator approximation,- Non-Lagrange interpolation,- Generic Karhunen-Loeve transform- Generalised low-rank matrix approximation- Optimal data compression- Optimal nonlinear filtering
