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Visualization eBooks

Learning Predictive Analytics with R Learning Predictive Analytics with R

R is statistical software that is used for data analysis. There are two main types of learning from data: unsupervised learning, where the structure of data is extracted automatically; and supervised learning, where a labeled part of the data is used to learn the relationship or scores in a target attribute. As important information is often hidden in a lot of data, R helps to extract that information with its many standard and cutting-edge statistical functions. This book is packed with easy-to-follow guidelines that explain the workings of the many key data mining tools of R, which are used to discover knowledge from your data.
Gephi Cookbook Gephi Cookbook

Gephi is an open source, user-friendly network visualization and analysis tool that provides numerous powerful features, making it easy for novices to get to grips with graph analysis quickly. This book is your one-stop guide to learning Gephi's interactive networking and visualization alongside the graph theory concepts that drive them. Each recipe walks you through a task and explains why and how it works. Starting with installing Gephi, you will learn how to begin analyzing a graph using Gephi's various features. You will discover how to make informed decisions using layout algorithms and filters, and perform statistical analysis with real-world datasets. This guide is an invaluable resource if you would like to plunge into the network analysis domain without having to learn how to code.
OpenGL Data Visualization Cookbook OpenGL Data Visualization Cookbook

OpenGL is a great multi-platform, cross-language, and hardware-accelerated graphics interface for visualizing large 2D and 3D datasets. Data visualization has become increasingly challenging using conventional approaches as datasets become larger and larger, especially with the Big Data evolution. From a mobile device to a sophisticated high-performance computing cluster, OpenGL libraries provide developers with an easy-to-use interface to create stunning visuals in 3D in real time for a wide range of interactive applications. This book provides a series of easy-to-follow, hands-on tutorials to create appealing OpenGL-based visualization tools with minimal development time. We will first illustrate how to quickly set up the development environment in Windows, Mac OS X, and Linux. Next, we will demonstrate how to visualize data for a wide range of applications using OpenGL, starting from simple 2D datasets to increasingly complex 3D datasets with more advanced techniques. Each chapter addresses different visualization problems encountered in real life and introduces the relevant OpenGL features and libraries in a modular fashion.
Three.js Cookbook Three.js Cookbook

Modern browsers are becoming more powerful each year and in recent years have adopted WebGL as the standard to deliver 3D graphics in a browser. Beginning with some basic recipes to get you started, this book will guide you through the most important features that Three.js has to offer. You'll even learn how to quickly create new geometries from scratch. Solutions and methods that show you how to use HTML5 video and canvas as textures will follow on from this. By the end of the book, you'll be able to quickly add advanced features to your scene, improve the way users interact with your 3D scene, and make your scenes look stunning.
Lumion 3D Best Practices Lumion 3D Best Practices

Lumion is a real-time 3D technology that lets you create amazing visualizations without the need for long rendering hours. Lumion 3D Best Practices covers the most important Lumion features and techniques that can be incorporated in to any real production environment. Each chapter covers a different stage of a production workflow. The first two chapters provide a good foundation, in particular for when creating content for Lumion. Furthermore, the book provides an efficient workflow by covering two classic visualization scenes: interior and exterior scenes. You then get to know the best techniques to create physically based materials that boost the look and realism of any 3D scene. Special chapters are reserved to create efficient animations, still images and movies. By the end of this practical guide, users will be familiar with the professional and effective techniques to increase efficiency in producing high-end quality visualizations in Lumion.
Data Visualization with JavaScript Data Visualization with JavaScript

You've got data to communicate. But what kind of visualization do you choose, how do you build it, and how do you ensure that it's up to the demands of the Web? In Data Visualization with JavaScript, you'll learn how to use JavaScript, HTML, and CSS to build the most practical visualizations for your data. Step-by-step examples walk you through creating, integrating, and debugging different types of visualizations and will have you building basic visualizations, like bar, line, and scatter graphs, in no time. If you already know your way around building a web page but aren't quite sure how to build a good visualization Data Visualization with JavaScript will help you get your feet wet without throwing you into the deep end. Before you know it, you'll be well on your way to creating simple, powerful data visualizations.
Mastering Gephi Network Visualization Mastering Gephi Network Visualization

Mastering Gephi Network Visualization will take you through an overview of Gephi and network behavior, followed by detailed chapters addressing layouts, filtering, graph statistics, dynamic graphs, and more. You will begin with a concise overview of working with the Gephi interface. You will then see how to create your own graphs and understand the graph layouts to arrange a sample dataset. You will understand the theory behind Dynamic Network Analysis, followed by sample applications on how Gephi can be used to model these networks. You will also learn about the plugins that are most critical for network analysis and graph creation. Finally, you will put together all the previously learned concepts and gain insight on the future state of network graph analysis. After reading this book and following the examples provided, you will have the confidence and expertise to create your own compelling graphs.
The Visual Organization The Visual Organization

The era of Big Data as arrived, and most organizations are woefully unprepared. Slowly, many are discovering that stalwarts like Excel spreadsheets, KPIs, standard reports, and even traditional business intelligence tools aren't sufficient. These old standbys can't begin to handle today's increasing streams, volumes, and types of data. In The Visual Organization, award-winning author and technology expert Phil Simon looks at how an increasingly number of organizations are embracing new dataviz tools and, more important, a new mind-set based upon data discovery and exploration. Simon adroitly shows how Amazon, Apple, Facebook, Google, Twitter, and other tech heavyweights use powerful data visualization tools to garner fascinating insights into their businesses. But make no mistake: these companies are hardly alone. Organizations of all types, industries, sizes are representing their data in new and amazing ways. As a result, they are asking better questions and making better business decisions.
IPython Interactive Computing and Visualization Cookbook IPython Interactive Computing and Visualization Cookbook

IPython is at the heart of the Python scientific stack. With its widely acclaimed web-based notebook, IPython is today an ideal gateway to data analysis and numerical computing in Python. IPython Interactive Computing and Visualization Cookbook contains many ready-to-use focused recipes for high-performance scientific computing and data analysis. The first part covers programming techniques, including code quality and reproducibility; code optimization; high-performance computing through dynamic compilation, parallel computing, and graphics card programming. The second part tackles data science, statistics, machine learning, signal and image processing, dynamical systems, and pure and applied mathematics.
Learning Python Data Visualization Learning Python Data Visualization

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 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.
Learning D3.js Mapping Learning D3.js Mapping

D3.js is a visualization library used for the creation and control of dynamic and interactive graphical forms. It is a library used to manipulate HTML and SVG documents based on data. A consolidated resource on obtaining geographic data, modifying it to your convenience, and visualizing it with augmented data using D3.js, this book will meet your mapping needs. Starting with a working map, you will explore the tools required to start the construction process, further moving on to cover the fundamentals of SVG and understanding its relation to creating maps using D3. Equipped with this overview, you will learn to make optimum use of D3's mapping, covering the main enter, update, and exit methods that allow D3.js to do its magic. Dealing with data joining and pairing with HTML and SVG, you will be introduced to different aspects of GEO data, along with the common file formats and converting data into GeoJSON and TopoJSON. You will learn to apply interactivity to your maps and create stunning visualizations before finally ensuring problem-free development with a chapter on troubleshooting.
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