Explorations In The Mathematics Of Data Science
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Explorations In The Mathematics Of Data Science
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Author : Simon Foucart
language : en
Publisher: Springer Nature
Release Date : 2024-09-12
Explorations In The Mathematics Of Data Science written by Simon Foucart and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-12 with Mathematics categories.
This edited volume reports on the recent activities of the new Center for Approximation and Mathematical Data Analytics (CAMDA) at Texas A&M University. Chapters are based on talks from CAMDA’s inaugural conference – held in May 2023 – and its seminar series, as well as work performed by members of the Center. They showcase the interdisciplinary nature of data science, emphasizing its mathematical and theoretical foundations, especially those rooted in approximation theory.
Foundations Of Data Science
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Author : Avrim Blum
language : en
Publisher: Cambridge University Press
Release Date : 2020-01-23
Foundations Of Data Science written by Avrim Blum 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 2020-01-23 with Computers categories.
Covers mathematical and algorithmic foundations of data science: machine learning, high-dimensional geometry, and analysis of large networks.
Advances In Data Science
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Author : Ilke Demir
language : en
Publisher: Springer Nature
Release Date : 2021-12-03
Advances In Data Science written by Ilke Demir and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-03 with Mathematics categories.
This volume highlights recent advances in data science, including image processing and enhancement on large data, shape analysis and geometry processing in 2D/3D, exploration and understanding of neural networks, and extensions to atypical data types such as social and biological signals. The contributions are based on discussions from two workshops under Association for Women in Mathematics (AWM), namely the second Women in Data Science and Mathematics (WiSDM) Research Collaboration Workshop that took place between July 29 and August 2, 2019 at the Institute for Computational and Experimental Research in Mathematics (ICERM) in Providence, Rhode Island, and the third Women in Shape (WiSh) Research Collaboration Workshop that took place between July 16 and 20, 2018 at Trier University in Robert-Schuman-Haus, Trier, Germany. These submissions, seeded by working groups at the conference, form a valuable source for readers who are interested in ideas and methods developed in interdisciplinary research fields. The book features ideas, methods, and tools developed through a broad range of domains, ranging from theoretical analysis on graph neural networks to applications in health science. It also presents original results tackling real-world problems that often involve complex data analysis on large multi-modal data sources.
Statistical Foundations Of Data Science
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Author : Jianqing Fan
language : en
Publisher: CRC Press
Release Date : 2020-09-21
Statistical Foundations Of Data Science written by Jianqing Fan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-21 with Mathematics categories.
Statistical Foundations of Data Science gives a thorough introduction to commonly used statistical models, contemporary statistical machine learning techniques and algorithms, along with their mathematical insights and statistical theories. It aims to serve as a graduate-level textbook and a research monograph on high-dimensional statistics, sparsity and covariance learning, machine learning, and statistical inference. It includes ample exercises that involve both theoretical studies as well as empirical applications. The book begins with an introduction to the stylized features of big data and their impacts on statistical analysis. It then introduces multiple linear regression and expands the techniques of model building via nonparametric regression and kernel tricks. It provides a comprehensive account on sparsity explorations and model selections for multiple regression, generalized linear models, quantile regression, robust regression, hazards regression, among others. High-dimensional inference is also thoroughly addressed and so is feature screening. The book also provides a comprehensive account on high-dimensional covariance estimation, learning latent factors and hidden structures, as well as their applications to statistical estimation, inference, prediction and machine learning problems. It also introduces thoroughly statistical machine learning theory and methods for classification, clustering, and prediction. These include CART, random forests, boosting, support vector machines, clustering algorithms, sparse PCA, and deep learning.
The Mathematical Heritage Of Guido Weiss
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Author : Eugenio Hernández
language : en
Publisher: Springer Nature
Release Date : 2025-01-31
The Mathematical Heritage Of Guido Weiss written by Eugenio Hernández and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-31 with Mathematics categories.
This work is a tribute to the life and work of Guido Weiss, a mathematician whose profound contributions shaped the field of harmonic analysis over a span of more than six decades. His groundbreaking research, from pioneering real and complex analysis to his later work on wavelets, continues to influence generations of scholars. More than just a researcher, Guido was a mentor, collaborator, and friend to many, creating a global community of mathematicians. His charisma and generosity fostered lasting professional and personal connections across continents, touching lives far beyond academia. This volume features contributions of collaborators, students, and colleagues of Guido, who had a particularly intense relationship with him. From a heartfelt remembrance of Guido Weiss to advanced discussions on spectral synthesis and wavelet theory, this collection contains a diverse landscape of mathematical results. Readers will delve into topics such as the compactness of bilinear commutators, the intricacies of analytic families in extrapolation theory, and the intersections of time-frequency analysis with modern learning techniques. With contributions to Hardy spaces, Haar multipliers, and crystalline measures, this book serves both as a tribute to past achievements and a beacon for future exploration.
Mathematical Masterpieces An Exploration Through History And Applications
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Author : Pasquale De Marco
language : en
Publisher: Pasquale De Marco
Release Date : 2025-04-22
Mathematical Masterpieces An Exploration Through History And Applications written by Pasquale De Marco and has been published by Pasquale De Marco this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-22 with Mathematics categories.
Mathematical Masterpieces: An Exploration Through History and Applications is a comprehensive and captivating exploration of the fascinating world of mathematics. This book is written in a clear and engaging style, making it accessible to readers of all backgrounds. Through a series of thought-provoking chapters, Mathematical Masterpieces: An Exploration Through History and Applications delves into the fundamental concepts that have shaped the development of mathematics over the centuries. Readers will embark on a journey that spans from the ancient Greeks' pioneering work on geometry and number theory to the groundbreaking discoveries of modern mathematicians. Along the way, they will encounter the brilliant minds that have illuminated the mathematical landscape, from Pythagoras and Euclid to Newton and Einstein. Beyond its historical significance, Mathematical Masterpieces: An Exploration Through History and Applications also explores the practical applications of mathematics in countless fields. Readers will discover how mathematics is used to solve real-world problems, drive innovation, and shape our daily lives. From engineering and medicine to finance and computer science, the book showcases the myriad ways in which mathematics empowers us to understand and interact with the world around us. But Mathematical Masterpieces: An Exploration Through History and Applications is not just about the practical applications of mathematics. It also delves into the philosophical implications of this remarkable field. Readers will explore the nature of mathematical truth, the relationship between mathematics and reality, and the ethical implications of using mathematical knowledge. These discussions provide a profound appreciation for the beauty, power, and transformative nature of mathematics. Whether you are a seasoned mathematician, a curious student, or simply someone who wants to expand their knowledge of this remarkable field, Mathematical Masterpieces: An Exploration Through History and Applications offers a captivating journey through the world of mathematics. Join us as we uncover the secrets of this fascinating subject and discover its profound impact on our understanding of the universe. If you like this book, write a review on google books!
Mathematical Foundations Of Scientific Visualization Computer Graphics And Massive Data Exploration
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Author : Torsten Möller
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-06-12
Mathematical Foundations Of Scientific Visualization Computer Graphics And Massive Data Exploration written by Torsten Möller 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 2009-06-12 with Computers categories.
The goal of visualization is the accurate, interactive, and intuitive presentation of data. Complex numerical simulations, high-resolution imaging devices and incre- ingly common environment-embedded sensors are the primary generators of m- sive data sets. Being able to derive scienti?c insight from data increasingly depends on having mathematical and perceptual models to provide the necessary foundation for effective data analysis and comprehension. The peer-reviewed state-of-the-art research papers included in this book focus on continuous data models, such as is common in medical imaging or computational modeling. From the viewpoint of a visualization scientist, we typically collaborate with an application scientist or engineer who needs to visually explore or study an object which is given by a set of sample points, which originally may or may not have been connected by a mesh. At some point, one generally employs low-order piecewise polynomial approximationsof an object, using one or several dependent functions. In order to have an understanding of a higher-dimensional geometrical “object” or function, ef?cient algorithms supporting real-time analysis and manipulation (- tation, zooming) are needed. Often, the data represents 3D or even time-varying 3D phenomena (such as medical data), and the access to different layers (slices) and structures (the underlying topology) comprising such data is needed.
Mathematics For Machine Learning
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Author : Marc Peter Deisenroth
language : en
Publisher: Cambridge University Press
Release Date : 2020-04-23
Mathematics For Machine Learning written by Marc Peter Deisenroth 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 2020-04-23 with Computers categories.
Distills key concepts from linear algebra, geometry, matrices, calculus, optimization, probability and statistics that are used in machine learning.
The Mathematics Of Data
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Author : Michael W. Mahoney
language : en
Publisher: American Mathematical Soc.
Release Date : 2018-11-15
The Mathematics Of Data written by Michael W. Mahoney and has been published by American Mathematical Soc. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-15 with Computers categories.
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Computing Mathematics
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Author : Barrett Williams
language : en
Publisher: Barrett Williams
Release Date : 2025-05-13
Computing Mathematics written by Barrett Williams and has been published by Barrett Williams this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-13 with Technology & Engineering categories.
Step into the captivating world of "Computing Mathematics," a journey where the timeless elegance of mathematics meets the cutting-edge realm of modern computing. This eBook takes you through a meticulously curated exploration of the indispensable mathematical concepts and frameworks that drive today’s technological advancements. Begin by unraveling the intriguing "Foundations of Mathematical Computation," a section that lays the groundwork with historical insights and essential theories. Dive into the birth of algorithmic thinking, encountering groundbreaking ideas that shaped the digital landscape, from Alan Turing's pioneering work to contemporary algorithm design and efficiency. Navigate through "Numerical Methods in Computing" and witness how equations and approximations fuel computational processes across various industries. Discover the power of cryptography in securing global communication, understanding both the elegance of mathematical encryption and complex cryptographic protocols. Venture into the realm of "Machine Learning and Statistical Methods," where algorithms and neural networks underpin the revolution in artificial intelligence. Explore graph theory’s pivotal role in mapping social networks and network analysis, offering fresh perspectives on connectivity and innovation. With a keen eye on future possibilities, the section on "Quantum Computing" invites you to imagine a novel computational paradigm, uniting quantum mechanics with algorithmic brilliance. Delve into the unpredictable world of chaos theory, learning its applications in predictive models and beyond. The eBook also shines a light on the vast potential of "Big Data and Data Science," offering insights into mathematical tools that decode the complexities of data-driven industries. Traverse through the intricate geometry in computational graphics and the foundational theories that anchor distributed systems and blockchain technologies. Conclude your expedition with "Future Directions," a visionary glance at the evolving nexus between mathematics and computing, where emerging trends and ethical considerations signal the next wave of innovation. "Computing Mathematics" is your gateway to understanding the mathematical heartbeat of the digital age—a must-read for anyone poised to embrace the future of technology.