Data Sketches

Author: Nadieh Bremer
Publisher: CRC Press
ISBN: 0429816820
Category : Computers
Languages : en
Pages : 429

Book Description
In Data Sketches, Nadieh Bremer and Shirley Wu document the deeply creative process behind 24 unique data visualization projects, and they combine this with powerful technical insights which reveal the mindset behind coding creatively. Exploring 12 different themes – from the Olympics to Presidents & Royals and from Movies to Myths & Legends – each pair of visualizations explores different technologies and forms, blurring the boundary between visualization as an exploratory tool and an artform in its own right. This beautiful book provides an intimate, behind-the-scenes account of all 24 projects and shares the authors’ personal notes and drafts every step of the way. The book features: Detailed information on data gathering, sketching, and coding data visualizations for the web, with screenshots of works-in-progress and reproductions from the authors’ notebooks Never-before-published technical write-ups, with beginner-friendly explanations of core data visualization concepts Practical lessons based on the data and design challenges overcome during each project Full-color pages, showcasing all 24 final data visualizations This book is perfect for anyone interested or working in data visualization and information design, and especially those who want to take their work to the next level and are inspired by unique and compelling data-driven storytelling.

Data Sketches

Author: Nadieh Bremer
Publisher: CRC Press
ISBN: 0429816839
Category : Computers
Languages : en
Pages : 428

Data Sketches

Author: Nadieh Bremer
Publisher: AK Peters Visualization Series
ISBN: 9780367000080
Category : Charts, diagrams, etc
Languages : en
Pages : 428

Book Description
Data visualization is an essential means of making visible the invisible patterns that surround us, and of seeing beyond the numbers. In Data Sketches, Nadieh Bremer and Shirley Wu document the deeply collaborative, deeply creative process behind 24 unique data visualization projects. Completed over the course of 12 months and spanning 12 different topics - from the Olympics to Presidents & Royals and from Movies to Myths & Legends - each pair of "wondrously eccentric" visualizations explores different technologies and forms, blurring the boundary between visualization as an exploratory tool and an art form in its own right. The book provides an intimate, behind-the-scenes account of all 24 projects - from data gathering, to sketching, to coding processes - and shares the authors' personal notes and drafts every step of the way. The book features: Detailed information on data gathering, sketching, and implementing processes, with screenshots of works-in-progress and reproductions from the authors' notebooks Never-before-published technical write-ups, with beginner-friendly explanations of core data visualization concepts Practical lessons based on the data and design challenges behind each project: the mistakes that were made and how they were overcome Full-color pages, showcasing all 24 final data visualizations An interview between the authors and series editor Tamara Munzner This book is perfect for anyone interested or working in data visualization and information design, especially those who want to take their work to the next level and are inspired by unique and compelling data-driven storytelling. Nadieh Bremer is an astronomer turned data scientist turned freelancing data visualization designer. Shirley Wu studied business and finance, graduated as a software engineer, and is now an independent data visualization designer. Connected by a mutual love for visualizing data, they bring a unique approach to visualization and refuse to be tied down by convention and available tools. The results are beautiful, innovative, and inspiring. They are both award-winning and internationally recognized data visualization designers. Their past clients include Google, UNESCO, SFMOMA, and the New York Times.

Dear Data

Author: Giorgia Lupi
Publisher: Chronicle Books
ISBN: 1616895462
Category : Design
Languages : en
Pages : 304

Book Description
Equal parts mail art, data visualization, and affectionate correspondence, Dear Data celebrates "the infinitesimal, incomplete, imperfect, yet exquisitely human details of life," in the words of Maria Popova (Brain Pickings), who introduces this charming and graphically powerful book. For one year, Giorgia Lupi, an Italian living in New York, and Stefanie Posavec, an American in London, mapped the particulars of their daily lives as a series of hand-drawn postcards they exchanged via mail weekly—small portraits as full of emotion as they are data, both mundane and magical. Dear Data reproduces in pinpoint detail the full year's set of cards, front and back, providing a remarkable portrait of two artists connected by their attention to the details of their lives—including complaints, distractions, phone addictions, physical contact, and desires. These details illuminate the lives of two remarkable young women and also inspire us to map our own lives, including specific suggestions on what data to draw and how. A captivating and unique book for designers, artists, correspondents, friends, and lovers everywhere.

Synopses for Massive Data

Author: Graham Cormode
Publisher: Now Publishers
ISBN: 9781601985163
Category : Computers
Languages : en
Pages : 308

Book Description
Describes basic principles and recent developments in approximate query processing. It focuses on four key synopses: random samples, histograms, wavelets, and sketches. It considers issues such as accuracy, space and time efficiency, optimality, practicality, range of applicability, error bounds on query answers, and incremental maintenance.

Info We Trust

Author: RJ Andrews
Publisher: John Wiley & Sons
ISBN: 1119483905
Category : Computers
Languages : en
Pages : 343

Book Description
How do we create new ways of looking at the world? Join award-winning data storyteller RJ Andrews as he pushes beyond the usual how-to, and takes you on an adventure into the rich art of informing. Creating Info We Trust is a craft that puts the world into forms that are strong and true. It begins with maps, diagrams, and charts — but must push further than dry defaults to be truly effective. How do we attract attention? How can we offer audiences valuable experiences worth their time? How can we help people access complexity? Dark and mysterious, but full of potential, data is the raw material from which new understanding can emerge. Become a hero of the information age as you learn how to dip into the chaos of data and emerge with new understanding that can entertain, improve, and inspire. Whether you call the craft data storytelling, data visualization, data journalism, dashboard design, or infographic creation — what matters is that you are courageously confronting the chaos of it all in order to improve how people see the world. Info We Trust is written for everyone who straddles the domains of data and people: data visualization professionals, analysts, and all who are enthusiastic for seeing the world in new ways. This book draws from the entirety of human experience, quantitative and poetic. It teaches advanced techniques, such as visual metaphor and data transformations, in order to create more human presentations of data. It also shows how we can learn from print advertising, engineering, museum curation, and mythology archetypes. This human-centered approach works with machines to design information for people. Advance your understanding beyond by learning from a broad tradition of putting things “in formation” to create new and wonderful ways of opening our eyes to the world. Info We Trust takes a thoroughly original point of attack on the art of informing. It builds on decades of best practices and adds the creative enthusiasm of a world-class data storyteller. Info We Trust is lavishly illustrated with hundreds of original compositions designed to illuminate the craft, delight the reader, and inspire a generation of data storytellers.

Small Summaries for Big Data

Author: Graham Cormode
Publisher: Cambridge University Press
ISBN: 1108477445
Category : Computers
Languages : en
Pages : 279

Book Description
A comprehensive introduction to flexible, efficient tools for describing massive data sets to improve the scalability of data analysis.

Machine Learning for Data Streams

Author: Albert Bifet
Publisher: MIT Press
ISBN: 0262346052
Category : Computers
Languages : en
Pages : 255

Book Description
A hands-on approach to tasks and techniques in data stream mining and real-time analytics, with examples in MOA, a popular freely available open-source software framework. Today many information sources—including sensor networks, financial markets, social networks, and healthcare monitoring—are so-called data streams, arriving sequentially and at high speed. Analysis must take place in real time, with partial data and without the capacity to store the entire data set. This book presents algorithms and techniques used in data stream mining and real-time analytics. Taking a hands-on approach, the book demonstrates the techniques using MOA (Massive Online Analysis), a popular, freely available open-source software framework, allowing readers to try out the techniques after reading the explanations. The book first offers a brief introduction to the topic, covering big data mining, basic methodologies for mining data streams, and a simple example of MOA. More detailed discussions follow, with chapters on sketching techniques, change, classification, ensemble methods, regression, clustering, and frequent pattern mining. Most of these chapters include exercises, an MOA-based lab session, or both. Finally, the book discusses the MOA software, covering the MOA graphical user interface, the command line, use of its API, and the development of new methods within MOA. The book will be an essential reference for readers who want to use data stream mining as a tool, researchers in innovation or data stream mining, and programmers who want to create new algorithms for MOA.

Foundations of Data Science

Author: Avrim Blum
Publisher: Cambridge University Press
ISBN: 1108617360
Category : Computers
Languages : en
Pages : 433

Book Description
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.

An Invitation to Applied Category Theory

Author: Brendan Fong
Publisher: Cambridge University Press
ISBN: 1108582249
Category : Mathematics
Languages : en
Pages : 351

Book Description
Category theory is unmatched in its ability to organize and layer abstractions and to find commonalities between structures of all sorts. No longer the exclusive preserve of pure mathematicians, it is now proving itself to be a powerful tool in science, informatics, and industry. By facilitating communication between communities and building rigorous bridges between disparate worlds, applied category theory has the potential to be a major organizing force. This book offers a self-contained tour of applied category theory. Each chapter follows a single thread motivated by a real-world application and discussed with category-theoretic tools. We see data migration as an adjoint functor, electrical circuits in terms of monoidal categories and operads, and collaborative design via enriched profunctors. All the relevant category theory, from simple to sophisticated, is introduced in an accessible way with many examples and exercises, making this an ideal guide even for those without experience of university-level mathematics.