The Shape of Data PDF Download

Author: Colleen M. Farrelly
Publisher: No Starch Press
ISBN: 1718503083
Category : Computers
Languages : en
Pages : 265

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Book Description
This advanced machine learning book highlights many algorithms from a geometric perspective and introduces tools in network science, metric geometry, and topological data analysis through practical application. Whether you’re a mathematician, seasoned data scientist, or marketing professional, you’ll find The Shape of Data to be the perfect introduction to the critical interplay between the geometry of data structures and machine learning. This book’s extensive collection of case studies (drawn from medicine, education, sociology, linguistics, and more) and gentle explanations of the math behind dozens of algorithms provide a comprehensive yet accessible look at how geometry shapes the algorithms that drive data analysis. In addition to gaining a deeper understanding of how to implement geometry-based algorithms with code, you’ll explore: Supervised and unsupervised learning algorithms and their application to network data analysis The way distance metrics and dimensionality reduction impact machine learning How to visualize, embed, and analyze survey and text data with topology-based algorithms New approaches to computational solutions, including distributed computing and quantum algorithms

Author: Anuj Srivastava
Publisher: Springer
ISBN: 1493940201
Category : Mathematics
Languages : en
Pages : 454

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Book Description
This textbook for courses on function data analysis and shape data analysis describes how to define, compare, and mathematically represent shapes, with a focus on statistical modeling and inference. It is aimed at graduate students in analysis in statistics, engineering, applied mathematics, neuroscience, biology, bioinformatics, and other related areas. The interdisciplinary nature of the broad range of ideas covered—from introductory theory to algorithmic implementations and some statistical case studies—is meant to familiarize graduate students with an array of tools that are relevant in developing computational solutions for shape and related analyses. These tools, gleaned from geometry, algebra, statistics, and computational science, are traditionally scattered across different courses, departments, and disciplines; Functional and Shape Data Analysis offers a unified, comprehensive solution by integrating the registration problem into shape analysis, better preparing graduate students for handling future scientific challenges. Recently, a data-driven and application-oriented focus on shape analysis has been trending. This text offers a self-contained treatment of this new generation of methods in shape analysis of curves. Its main focus is shape analysis of functions and curves—in one, two, and higher dimensions—both closed and open. It develops elegant Riemannian frameworks that provide both quantification of shape differences and registration of curves at the same time. Additionally, these methods are used for statistically summarizing given curve data, performing dimension reduction, and modeling observed variability. It is recommended that the reader have a background in calculus, linear algebra, numerical analysis, and computation.

Author: Colleen M. Farrelly
Publisher: No Starch Press
ISBN: 1718503091
Category : Computers
Languages : en
Pages : 265

View

Book Description
This advanced machine learning book highlights many algorithms from a geometric perspective and introduces tools in network science, metric geometry, and topological data analysis through practical application. Whether you’re a mathematician, seasoned data scientist, or marketing professional, you’ll find The Shape of Data to be the perfect introduction to the critical interplay between the geometry of data structures and machine learning. This book’s extensive collection of case studies (drawn from medicine, education, sociology, linguistics, and more) and gentle explanations of the math behind dozens of algorithms provide a comprehensive yet accessible look at how geometry shapes the algorithms that drive data analysis. In addition to gaining a deeper understanding of how to implement geometry-based algorithms with code, you’ll explore: Supervised and unsupervised learning algorithms and their application to network data analysis The way distance metrics and dimensionality reduction impact machine learning How to visualize, embed, and analyze survey and text data with topology-based algorithms New approaches to computational solutions, including distributed computing and quantum algorithms

Author: Julia Flanders
Publisher: Routledge
ISBN: 1317016149
Category : Language Arts & Disciplines
Languages : en
Pages : 382

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Book Description
Data and its technologies now play a large and growing role in humanities research and teaching. This book addresses the needs of humanities scholars who seek deeper expertise in the area of data modeling and representation. The authors, all experts in digital humanities, offer a clear explanation of key technical principles, a grounded discussion of case studies, and an exploration of important theoretical concerns. The book opens with an orientation, giving the reader a history of data modeling in the humanities and a grounding in the technical concepts necessary to understand and engage with the second part of the book. The second part of the book is a wide-ranging exploration of topics central for a deeper understanding of data modeling in digital humanities. Chapters cover data modeling standards and the role they play in shaping digital humanities practice, traditional forms of modeling in the humanities and how they have been transformed by digital approaches, ontologies which seek to anchor meaning in digital humanities resources, and how data models inhabit the other analytical tools used in digital humanities research. It concludes with a glossary chapter that explains specific terms and concepts for data modeling in the digital humanities context. This book is a unique and invaluable resource for teaching and practising data modeling in a digital humanities context.

Author: Julia Flanders
Publisher: Routledge
ISBN: 1317016157
Category : Language Arts & Disciplines
Languages : en
Pages : 342

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Book Description
Data and its technologies now play a large and growing role in humanities research and teaching. This book addresses the needs of humanities scholars who seek deeper expertise in the area of data modeling and representation. The authors, all experts in digital humanities, offer a clear explanation of key technical principles, a grounded discussion of case studies, and an exploration of important theoretical concerns. The book opens with an orientation, giving the reader a history of data modeling in the humanities and a grounding in the technical concepts necessary to understand and engage with the second part of the book. The second part of the book is a wide-ranging exploration of topics central for a deeper understanding of data modeling in digital humanities. Chapters cover data modeling standards and the role they play in shaping digital humanities practice, traditional forms of modeling in the humanities and how they have been transformed by digital approaches, ontologies which seek to anchor meaning in digital humanities resources, and how data models inhabit the other analytical tools used in digital humanities research. It concludes with a glossary chapter that explains specific terms and concepts for data modeling in the digital humanities context. This book is a unique and invaluable resource for teaching and practising data modeling in a digital humanities context.

Author: Kitchin, Rob
Publisher: Policy Press
ISBN: 1529215153
Category : Social Science
Languages : en
Pages : 274

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Book Description
The word ‘data’ has entered everyday conversation, but do we really understand what it means? How can we begin to grasp the scope and scale of our new data-rich world, and can we truly comprehend what is at stake? In Data Lives, renowned social scientist Rob Kitchin explores the intricacies of data creation and charts how data-driven technologies have become essential to how society, government and the economy work. Creatively blending scholarly analysis, biography and fiction, he demonstrates how data are shaped by social and political forces, and the extent to which they influence our daily lives. He reveals our data world to be one of potential danger, but also of hope.

Author: Tomasz Tunguz
Publisher: John Wiley & Sons
ISBN: 1119257239
Category : Business & Economics
Languages : en
Pages : 179

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Book Description
Crest the data wave with a deep cultural shift Winning with Data explores the cultural changes big data brings to business, and shows you how to adapt your organization to leverage data to maximum effect. Authors Tomasz Tunguz and Frank Bien draw on extensive background in big data, business intelligence, and business strategy to provide a blueprint for companies looking to move head-on into the data wave. Instrumentation is discussed in detail, but the core of the change is in the culture—this book provides sound guidance on building the type of organizational culture that creates and leverages data daily, in every aspect of the business. Real-world examples illustrate these important concepts at work: you'll learn how data helped Warby-Parker disrupt a $13 billion monopolized market, how ThredUp uses data to process more than 20 thousand items of clothing every day, how Venmo leverages data to build better products, how HubSpot empowers their salespeople to be more productive, and more. From decision making and strategy to shipping and sales, this book shows you how data makes better business. Big data has taken on buzzword status, but there is little real guidance for companies seeking everyday business data solutions. This book takes a deeper look at big data in business, and shows you how to shift internal culture ahead of the curve. Understand the changes a data culture brings to companies Instrument your company for maximum benefit Utilize data to optimize every aspect of your business Improve decision making and transform business strategy Big data is becoming the number-one topic in business, yet no one is asking the right questions. Leveraging the full power of data requires more than good IT—organization-wide buy-in is essential for long-term success. Winning with Data is the expert guide to making data work for your business, and your needs.

Author: Tim Harford
Publisher: Penguin
ISBN: 0593084675
Category : Business & Economics
Languages : en
Pages : 336

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Book Description
From “one of the great (greatest?) contemporary popular writers on economics” (Tyler Cowen) comes a smart, lively, and encouraging rethinking of how to use statistics. Today we think statistics are the enemy, numbers used to mislead and confuse us. That’s a mistake, Tim Harford says in The Data Detective. We shouldn’t be suspicious of statistics—we need to understand what they mean and how they can improve our lives: they are, at heart, human behavior seen through the prism of numbers and are often “the only way of grasping much of what is going on around us.” If we can toss aside our fears and learn to approach them clearly—understanding how our own preconceptions lead us astray—statistics can point to ways we can live better and work smarter. As “perhaps the best popular economics writer in the world” (New Statesman), Tim Harford is an expert at taking complicated ideas and untangling them for millions of readers. In The Data Detective, he uses new research in science and psychology to set out ten strategies for using statistics to erase our biases and replace them with new ideas that use virtues like patience, curiosity, and good sense to better understand ourselves and the world. As a result, The Data Detective is a big-idea book about statistics and human behavior that is fresh, unexpected, and insightful.

Author: Christopher G. Small
Publisher: Springer Science & Business Media
ISBN: 1461240328
Category : Mathematics
Languages : en
Pages : 237

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Book Description
In general terms, the shape of an object, data set, or image can be de fined as the total of all information that is invariant under translations, rotations, and isotropic rescalings. Thus two objects can be said to have the same shape if they are similar in the sense of Euclidean geometry. For example, all equilateral triangles have the same shape, and so do all cubes. In applications, bodies rarely have exactly the same shape within measure ment error. In such cases the variation in shape can often be the subject of statistical analysis. The last decade has seen a considerable growth in interest in the statis tical theory of shape. This has been the result of a synthesis of a number of different areas and a recognition that there is considerable common ground among these areas in their study of shape variation. Despite this synthesis of disciplines, there are several different schools of statistical shape analysis. One of these, the Kendall school of shape analysis, uses a variety of mathe matical tools from differential geometry and probability, and is the subject of this book. The book does not assume a particularly strong background by the reader in these subjects, and so a brief introduction is provided to each of these topics. Anyone who is unfamiliar with this material is advised to consult a more complete reference. As the literature on these subjects is vast, the introductory sections can be used as a brief guide to the literature.

Author: Kris Shaffer
Publisher: Apress
ISBN: 9781484245392
Category : Computers
Languages : en
Pages : 120

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Book Description
Human attention is in the highest demand it has ever been. The drastic increase in available information has compelled individuals to find a way to sift through the media that is literally at their fingertips. Content recommendation systems have emerged as the technological solution to this social and informational problem, but they’ve also created a bigger crisis in confirming our biases by showing us only, and exactly, what it predicts we want to see. Data versus Democracy investigates and explores how, in the era of social media, human cognition, algorithmic recommendation systems, and human psychology are all working together to reinforce (and exaggerate) human bias. The dangerous confluence of these factors is driving media narratives, influencing opinions, and possibly changing election results. In this book, algorithmic recommendations, clickbait, familiarity bias, propaganda, and other pivotal concepts are analyzed and then expanded upon via fascinating and timely case studies: the 2016 US presidential election, Ferguson, GamerGate, international political movements, and more events that come to affect every one of us. What are the implications of how we engage with information in the digital age? Data versus Democracy explores this topic and an abundance of related crucial questions. We live in a culture vastly different from any that has come before. In a society where engagement is currency, we are the product. Understanding the value of our attention, how organizations operate based on this concept, and how engagement can be used against our best interests is essential in responsibly equipping ourselves against the perils of disinformation. Who This Book Is For Individuals who are curious about how social media algorithms work and how they can be manipulated to influence culture. Social media managers, data scientists, data administrators, and educators will find this book particularly relevant to their work.