Books: 56

Visualization

CoverTitleYear
Big Data of Complex Networks presents and explains the methods from the study of big data that can be used in analysing massive structural data sets, including both very large networks and sets of graphs. As well as applying statistical analysis techniques like sampling and bootstrapping in an interdisciplinary more » manner to produce novel techniques for analyzing massive amounts of data, this book also explores the possibilities offered by the special aspects such as computer memory in investigating large sets of complex networks. Intended for computer scientists, statisticians and mathematicians interested in the big data and networks, Big Data of Complex Networks is also a valuable tool for researchers in the fields of visualization, data analysis, computer vision and bioinformatics. Key features: * Provides a complete discussion of both the hardware and software used to organize big data * Describes a wide range of useful applications for managing big data and resultant data sets * Maintains a firm focus on massive data and large networks * Unveils innovative techniques to help readers handle big data Matthias Dehmer received his PhD in computer science from the Darmstadt University of Technology, Germany. Currently, he is Professor at UMIT – The Health and Life Sciences University, Austria, and the Universität der Bundeswehr München. His research interests are in graph theory, data science, complex networks, complexity, statistics and information theory. Frank Emmert-Streib received his PhD in theoretical physics from the University of Bremen, and is currently Associate professor at Tampere University of Technology, Finland. His research interests are in the field of computational biology, machine learning and network medicine. Stefan Pickl holds a PhD in mathematics from the Darmstadt University of Technology, and is currently a Professor at Bundeswehr Universität München. His research interests are in operations research, systems biology, graph theory and discrete optimization. Andreas Holzinger received his PhD in cognitive science from Graz University and his habilitation (second PhD) in computer science from Graz University of Technology. He is head of the Holzinger Group HCI-KDD at the Medical University Graz and Visiting Professor for Machine Learning in Health Informatics Vienna University of Technology. « less
2016
Take business intelligence delivery to a new level that is interactive, engaging, even fun, all while driving commercial success through sound decision making. Do this through the power of visualization using this updated edition covering new features and added support for visualization in Excel 2016, more » and describing the latest developments in Get & Transform and DAX. The example data set has also been updated to demonstrate all that Microsoft's self-service business intelligence suite is now capable of. Data Visualization in Excel 2016: Power View, 3D Maps, Get & Transform, and Power BI, 2nd Edition helps in harnessing the power of Microsoft’s flagship, self-service business intelligence suite to deliver compelling and interactive insight with remarkable ease. Learn the essential techniques needed to enhance the look and feel of reports and dashboards so that you can seize your audience’s attention and provide them with clear and accurate information. Also learn to integrate data from a variety of sources and create coherent data models displaying clear metrics and attributes. Power View is Microsoft's ground-breaking tool for ad-hoc data visualization and analysis. It's designed to produce elegant and visually arresting output. It's also built to enhance user experience through polished interactivity. Power Map is a similarly powerful mechanism for analyzing data across geographic and political units. Get & Transform lets you load, shape and streamline data from multiple sources. Power Pivot can extend and develop data into a dynamic model. Power BI allows you to share your findings with colleagues, and present your insights to clients. Data Visualization in Excel 2016: Power View, 3D Maps, Get & Transform, and Power BIhelps you master this suite of powerful tools from Microsoft. You'll learn to identify data sources, and to save time by preparing your underlying data correctly. You'll also learn to deliver your powerful visualizations and analyses through the cloud to PCs, tablets and smartphones. * Simple techniques take raw data and convert it into information. * Slicing and dicing metrics delivers interactive insight. * Visually arresting output grabs and focuses attention on key indicators. What You Will Learn * Produce designer output that will astound your bosses and peers. * Drive business intelligence from Excel using BI in the Cloud. * Gather source data from corporate and public sources. * Integrate charts, maps, and tables to deliver visually stunning information. * Discover new insights as you chop and tweak your data as never before. * Adapt delivery to mobile devices. * Outshine competing products and enhance existing skills. Who This Book Is For Data Visualization in Excel 2016: Power View, 3D Maps, Get & Transform, and Power BI, 2nd Edition is written for any Power BI Desktop, Excel or SharePoint user. Business Intelligence developers, power users, IT managers, finance experts, and more can use this book to outshine the competition by producing high-impact business intelligence reporting on a variety of devices from a variety of sources. « less
2016
Prevalent types of data in scientific visualization are volumetric data, vector field data, and particle-based data. Particle data typically originates from measurements and simulations in various fields, such as life sciences or physics. The particles are often visualized directly, that is, by simple more » representants like spheres. Interactive rendering facilitates the exploration and visual analysis of the data. With increasing data set sizes in terms of particle numbers, interactive high-quality visualization is a challenging task. This is especially true for dynamic data or abstract representations that are based on the raw particle data. This book covers direct particle visualization using simple glyphs as well as abstractions that are application-driven such as clustering and aggregation. It targets visualization researchers and developers who are interested in visualization techniques for large, dynamic particle-based data. Its explanations focus on GPU-accelerated algorithms for high-performance rendering and data processing that run in real-time on modern desktop hardware. Consequently, the implementation of said algorithms and the required data structures to make use of the capabilities of modern graphics APIs are discussed in detail. Furthermore, it covers GPU-accelerated methods for the generation of application-dependent abstract representations. This includes various representations commonly used in application areas such as structural biology, systems biology, thermodynamics, and astrophysics. « less
2016
Explore the world of data science from scratch with Julia by your side
KEY FEATURES * An in-depth exploration of Julia's growing ecosystem of packages * Work with the most powerful open-source libraries for deep learning, data wrangling, and data visualization * Learn about deep learning using Mocha.jl and give speed and high performance to data analysis on large data more » sets BOOK DESCRIPTION Julia is a fast and high performing language that's perfectly suited to data science with a mature package ecosystem and is now feature complete. It is a good tool for a data science practitioner. There was a famous post at Harvard Business Review that Data Scientist is the sexiest job of the 21st century. (https://hbr.org/2012/10/data-scientist-the-sexiest-job-of-the-21st-century). This book will help you get familiarised with Julia's rich ecosystem, which is continuously evolving, allowing you to stay on top of your game. This book contains the essentials of data science and gives a high-level overview of advanced statistics and techniques. You will dive in and will work on generating insights by performing inferential statistics, and will reveal hidden patterns and trends using data mining. This has the practical coverage of statistics and machine learning. You will develop knowledge to build statistical models and machine learning systems in Julia with attractive visualizations. You will then delve into the world of Deep learning in Julia and will understand the framework, Mocha.jl with which you can create artificial neural networks and implement deep learning. This book addresses the challenges of real-world data science problems, including data cleaning, data preparation, inferential statistics, statistical modeling, building high-performance machine learning systems and creating effective visualizations using Julia. WHAT YOU WILL LEARN * Apply statistical models in Julia for data-driven decisions * Understanding the process of data munging and data preparation using Julia * Explore techniques to visualize data using Julia and D3 based packages * Using Julia to create self-learning systems using cutting edge machine learning algorithms * Create supervised and unsupervised machine learning systems using Julia. Also, explore ensemble models * Build a recommendation engine in Julia * Dive into Julia’s deep learning framework and build a system using Mocha.jl ABOUT THE AUTHOR Anshul Joshi is a data science professional with more than 2 years of experience primarily in data munging, recommendation systems, predictive modeling, and distributed computing. He is a deep learning and AI enthusiast. Most of the time, he can be caught exploring GitHub or trying anything new on which he can get his hands on. He blogs on anshuljoshi.xyz. TABLE OF CONTENTS 1. The Groundwork – Julia's Environment 2. Data Munging 3. Data Exploration 4. Deep Dive into Inferential Statistics 5. Making Sense of Data Using Visualization 6. Supervised Machine Learning 7. Unsupervised Machine Learning 8. Creating Ensemble Models 9. Time Series 10. Collaborative Filtering and Recommendation System 11. Introduction to Deep Learning « less
2016
A Guide to the Technologies, Applications, and Human Factors for AR and VR
This is the most comprehensive and up-to-date guide to the technologies, applications and human factors considerations of Augmented Reality (AR) and Virtual Reality (VR) systems and wearable computing devices. Ideal for practitioners and students alike, it brings together comprehensive coverage of both more » theory and practice, emphasizing leading-edge displays, sensors, and other enabling technologies and tools that are already commercially available or will be soon. Beginning with a Foreword by NASA research scientist Victor Luo, Practical Augmented Reality starts by explaining the mechanics of human sight, hearing and touch, showing how these perceptual mechanisms (and their performance ranges) directly dictate the design and use of wearable displays, 3-D audio systems, and tactile/force feedback devices. The book presents revealing case studies of real-world applications from gaming, entertainment, Big Data visualization, engineering, aeronautics and aerospace, defense, medicine, telerobotics, architecture, law enforcement, and geophysics. Readers will find clear, easy-to-understand explanations, photos, and illustrations of devices including the Atheer AiR, HTC Vive, DAQRI Smart Helmet, Oculus (Facebook) CV1, Sony PlayStation VR, Vuzix M300, Google Glass, and many more. Functional diagrams and photographs clearly explain how these devices operate, and link directly to relevant theoretical and practical content. Practical Augmented Reality thoroughly considers the human factors of these systems, including sensory and motor physiology constraints, monocular and binocular depth cues, elements contributing to visually-induced motion sickness and nausea, as well as vergence-accommodation conflicts. It concludes by assessing both the legal and societal implications of new and emerging AR, VR, and wearable technologies, as well as provides a look next generation systems. « less
2016
Analyze your data and delve deep into the world of machine learning with the latest Spark version, 2.0
About This Book Perform data analysis and build predictive models on huge datasets that leverage Apache Spark Learn to integrate data science algorithms and techniques with the fast and scalable computing features of Spark to address big data challenges Work through practical examples on real-world more » problems with sample code snippets Who This Book Is For This book is for anyone who wants to leverage Apache Spark for data science and machine learning. If you are a technologist who wants to expand your knowledge to perform data science operations in Spark, or a data scientist who wants to understand how algorithms are implemented in Spark, or a newbie with minimal development experience who wants to learn about Big Data Analytics, this book is for you! What You Will Learn Consolidate, clean, and transform your data acquired from various data sources Perform statistical analysis of data to find hidden insights Explore graphical techniques to see what your data looks like Use machine learning techniques to build predictive models Build scalable data products and solutions Start programming using the RDD, DataFrame and Dataset APIs Become an expert by improving your data analytical skills In Detail This is the era of Big Data. The words ‘Big Data’implies big innovation and enables a competitive advantage for businesses. Apache Spark was designed to perform Big Data analytics at scale, and so Spark is equipped with the necessary algorithms and supports multiple programming languages. Whether you are a technologist, a data scientist, or a beginner to Big Data analytics, this book will provide you with all the skills necessary to perform statistical data analysis, data visualization, predictive modeling, and build scalable data products or solutions using Python, Scala, and R. « less
2016
Master how to build dynamic HTML5-ready SVG charts using Python and the pygal library
The best applications use data and present it in a meaningful, easy-to-understand way. Packed with sample code and tutorials, this book will walk you through installing common charts, graphics, and utility libraries for the Python programming language. Firstly you will discover how to install and more » reference libraries in Visual Studio or Eclipse. We will then go on to build simple graphics and charts that allow you to generate HTML5-ready SVG charts and graphs, along with testing and validating your data sources. We will also cover parsing data from the Web and offline sources, and building a Python charting application using dynamic data. Lastly, we will review other popular tools and frameworks used to create charts and import/export chart data. By the end of this book, you will be able to represent complex sets of data using Python. « less
2014
Flex your speed modeling muscles using 3ds Max
Is your 3D modeling up to speed? It soon will be with this brilliant practical guide to speed modeling with 3ds Max, focusing on hard surfaces. Raise your productivity a notch and gain a new level of professionalism. Overview * Learn to speed model in 3ds Max, with an emphasis on hard surfaces * more » Up to date coverage, covering 3ds Max 2013 features * Focused explanations with step-driven practical lessons balance learning and action What you will learn from this book * Modeling processes using the Ribbon * Ways to create a customized UI for accessing modeling tools faster * Modeling using modifiers and deformations * UV mapping and topology effect readiness for sculpting * How to work with GoZ and ZBrush * Procedures for painting models using Viewport Canvas * Concepts of game-readiness * Retopology and polygon reduction methods * Easy rigging, skinning and animation walk-throughs * Gain fluency in UV mapping and texture creation * How to render and present your models for your folio Approach Step by step illustrated tutorials are supported by a focused commentary. The examples are designed to proceed from starting to model through model finishing to putting models to work within projects and presentation. The book shows both - the entire flow of asset creation and granular methodology. Who this book is written for This book will appeal to anyone interested in 3D modeling who wants to improve their speed modeling ability, particularly artists whose work is relevant to industries where hard surface modeling or model prototyping is required, such as games, films, or visualization. IN DETAIL Production of 3D art is an exciting medium, but the task of modeling requires intense attention to detail, so speed and efficiency are vital. This book breaks down speed modeling workflow in 3ds Max into stages you can easily achieve, with a focus on hard surface modeling and methods you can apply to your own designs. "3ds Max Speed Modeling for Games" will help level up your 3D modeling skills. It focuses on hard surface modeling, and shows the range of tools and techniques in 3ds Max 2013. This book shows content creation methods aimed at 3ds Max modelers preparing to show their skill to the industry. The key feature of modeling that artists must exhibit is speediness while preserving technical accuracy. The author helps you follow set project guidelines while pushing creativity and outlines the entire workflow from concept development to exporting a game-ready model. The book begins with introductions for new users to the interface and modeling tools, and progresses to topics aimed at users already familiar with 3ds Max, who want to improve their content creation process. You'll also see ways 3ds Max content is used with other applications, like sculpting software and game editors, and learn features of speed modeling, efficient workflow, re-use of content, and tips on getting more done, more quickly. By the end of this book you will have learned key topics in modeling, ready to face professional level work with elan. « less
2012
Create 3D game worlds complete with textures, levels, and props
The book takes a clear, step-by-step approach to building a complete game level using SketchUp with many props and textures. This book is designed for anyone who wants to create entire 3D worlds in freely available game engines such as Unity 3D, CryEngine, Ogre, Panda3D, Unreal Engine, and Blender Game more » Engine. It also targets all those who wish to create new levels and assets to sell in game asset stores or use in visualization or animation. « less
2011
Windows Presentation Foundation in .NET 4
Microsoft's Windows Presentation Foundation (WPF) provides the foundation for building applications and high-quality user experiences for the Windows operating system. It blends the application user interface, documents, and media content, while exploiting the full power of your computer's operating more » system. Its functionality extends to the support for tablet PCs and other forms of input device, and it provides a more modern imaging and printing pipeline, accessibility and UI automation infrastructure, data-driven user interfaces and visualization, and integration points for weaving the application experience into the Windows shell. This book shows you how WPF really works. It provides you with the no-nonsense, practical advice that you need in order to build high-quality WPF applications quickly and easily. After giving you a firm foundation, it goes on to explore the more advance aspects of WPF and how they relate to the others elements of the .NET 4.0 platform and associated technologies such as Silverlight. « less
2010