Handbook of Analysis and Its Foundations
Title | Handbook of Analysis and Its Foundations PDF eBook |
Author | Eric Schechter |
Publisher | Academic Press |
Pages | 907 |
Release | 1996-10-24 |
Genre | Mathematics |
ISBN | 0080532993 |
Handbook of Analysis and Its Foundations is a self-contained and unified handbook on mathematical analysis and its foundations. Intended as a self-study guide for advanced undergraduates and beginning graduatestudents in mathematics and a reference for more advanced mathematicians, this highly readable book provides broader coverage than competing texts in the area. Handbook of Analysis and Its Foundations provides an introduction to a wide range of topics, including: algebra; topology; normed spaces; integration theory; topological vector spaces; and differential equations. The author effectively demonstrates the relationships between these topics and includes a few chapters on set theory and logic to explain the lack of examples for classical pathological objects whose existence proofs are not constructive. More complete than any other book on the subject, students will find this to be an invaluable handbook. Covers some hard-to-find results including: Bessagas and Meyers converses of the Contraction Fixed Point Theorem Redefinition of subnets by Aarnes and Andenaes Ghermans characterization of topological convergences Neumanns nonlinear Closed Graph Theorem van Maarens geometry-free version of Sperners Lemma Includes a few advanced topics in functional analysis Features all areas of the foundations of analysis except geometry Combines material usually found in many different sources, making this unified treatment more convenient for the user Has its own webpage: http://math.vanderbilt.edu/
The Foundations of Modern Time Series Analysis
Title | The Foundations of Modern Time Series Analysis PDF eBook |
Author | Terence C. Mills |
Publisher | Springer |
Pages | 476 |
Release | 2011-06-29 |
Genre | Business & Economics |
ISBN | 0230305024 |
This book develops the analysis of Time Series from its formal beginnings in the 1890s through to the publication of Box and Jenkins' watershed publication in 1970, showing how these methods laid the foundations for the modern techniques of Time Series analysis that are in use today.
Foundations of Factor Analysis
Title | Foundations of Factor Analysis PDF eBook |
Author | Stanley A Mulaik |
Publisher | CRC Press |
Pages | 550 |
Release | 2009-09-25 |
Genre | Mathematics |
ISBN | 1420099817 |
Providing a practical, thorough understanding of how factor analysis works, Foundations of Factor Analysis, Second Edition discusses the assumptions underlying the equations and procedures of this method. It also explains the options in commercial computer programs for performing factor analysis and structural equation modeling. This long-awaited e
Handbook of Research on Foundations and Applications of Intelligent Business Analytics
Title | Handbook of Research on Foundations and Applications of Intelligent Business Analytics PDF eBook |
Author | Sun, Zhaohao |
Publisher | IGI Global |
Pages | 425 |
Release | 2022-03-11 |
Genre | Computers |
ISBN | 179989018X |
Intelligent business analytics is an emerging technology that has become a mainstream market adopted broadly across industries, organizations, and geographic regions. Intelligent business analytics is a current focus for research and development across academia and industries and must be examined and considered thoroughly so businesses can apply the technology appropriately. The Handbook of Research on Foundations and Applications of Intelligent Business Analytics examines the technologies and applications of intelligent business analytics and discusses the foundations of intelligent analytics such as intelligent mining, intelligent statistical modeling, and machine learning. Covering topics such as augmented analytics and artificial intelligence systems, this major reference work is ideal for scholars, engineers, professors, practitioners, researchers, industry professionals, academicians, and students.
Homotopy Type Theory: Univalent Foundations of Mathematics
Title | Homotopy Type Theory: Univalent Foundations of Mathematics PDF eBook |
Author | |
Publisher | Univalent Foundations |
Pages | 484 |
Release | |
Genre | |
ISBN |
The Foundations of Real Analysis
Title | The Foundations of Real Analysis PDF eBook |
Author | Richard Mikula |
Publisher | Universal-Publishers |
Pages | 505 |
Release | 2015-10-20 |
Genre | Mathematics |
ISBN | 1627345655 |
This textbook covers the subject of real analysis from the fundamentals up through beginning graduate level. It is appropriate as an introductory course text or a review text for graduate qualifying examinations. Some special features of the text include a thorough discussion of transcendental functions such as trigonometric, logarithmic, and exponential from power series expansions, deducing all important functional properties from the series definitions. The text is written in a user-friendly manner, and includes full solutions to all assigned exercises throughout the text.
Foundations of Data Science
Title | Foundations of Data Science PDF eBook |
Author | Avrim Blum |
Publisher | Cambridge University Press |
Pages | 433 |
Release | 2020-01-23 |
Genre | Computers |
ISBN | 1108617360 |
This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix norms and VC-dimension. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data.