QGIS 2 CookbookQGIS is a user-friendly, cross-platform desktop geographic information system used to make maps and analyze spatial data. QGIS allows users to understand, question, interpret, and visualize spatial data in many ways that reveal relationships, patterns, and trends in the form of maps. This book is a collection of simple to advanced techniques that are needed in everyday geospatial work, and shows how to accomplish them with QGIS. You will begin by understanding the different types of data management techniques, as well as how data exploration works. You will then learn how to perform classic vector and raster analysis with QGIS, apart from creating time-based visualizations. Finally, you will learn how to create interactive and visually appealing maps with custom cartography. By the end of this book, you will have all the necessary knowledge to handle spatial data management, exploration, and visualization tasks in QGIS. ...
Data AlgorithmsIf you are ready to dive into the MapReduce framework for processing large datasets, this practical book takes you step by step through the algorithms and tools you need to build distributed MapReduce applications with Apache Hadoop or Apache Spark. Each chapter provides a recipe for solving a massive computational problem, such as building a recommendation system. You'll learn how to implement the appropriate MapReduce solution with code that you can use in your projects.
Dr. Mahmoud Parsian covers basic design patterns, optimization techniques, and data mining and machine learning solutions for problems in bioinformatics, genomics, statistics, and social network analysis. This book also includes an overview of MapReduce, Hadoop, and Spark. ...
Algorithms from and for Nature and LifeThis volume provides approaches and solutions to challenges occurring at the interface of research fields such as, e.g., data analysis, data mining and knowledge discovery, computer science, operations research, and statistics. In addition to theory-oriented contributions various application areas are included. Moreover, traditional classification research directions concerning network data, graphs, and social relationships as well as statistical musicology describe examples for current interest fields tackled by the authors. The book comprises a total of 55 selected papers presented at the Joint Conference of the German Classification Society (GfKl), the German Association for Pattern Recognition (DAGM), and the Symposium of the International Federation of Classification Societies (IFCS) in 2011. ...
Handbook of Data Compression, 5th EditionData compression is such an important tool in modern computing that some researchers even suggest that all computing is compression! This comprehensive fifth edition of David Salomon's highly successful reference, Data Compression, now fully reconceived under its new title, Handbook of Data Compression, is thoroughly updated with the latest progress in the field. This all-inclusive and user-friendly reference work discusses the wide range of compression methods for text, graphical data (still images and movies), and audio. ...
High Impact Data Visualization with Power View, Power Map, and Power BIHigh Impact Data Visualization with Power View, Power Map, and Power BI helps you take business intelligence delivery to a new level that is interactive, engaging, even fun, all while driving commercial success through sound decision-making. Learn to harness 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. ...
Energy Efficient ServersEnergy Efficient Servers: Blueprints for Data Center Optimization introduces engineers and IT professionals to the power management technologies and techniques used in energy efficient servers. The book includes a deep examination of different features used in processors, memory, interconnects, I/O devices, and other platform components. It outlines the power and performance impact of these features and the role firmware and software play in initialization and control. Using examples from cloud, HPC, and enterprise environments, the book demonstrates how various power management technologies are utilized across a range of server utilization. It teaches the reader how to monitor, analyze, and optimize their environment to best suit their needs. It shares optimization techniques used by data center administrators and system optimization experts at the world's most advanced data centers. ...
Data Structures and Algorithms with PythonThis book explains the concepts and techniques required to write programs that can handle large amounts of data efficiently. Project-oriented and classroom-tested, the book presents a number of important algorithms supported by examples that bring meaning to the problems faced by computer programmers. The idea of computational complexity is also introduced, demonstrating what can and cannot be computed efficiently so that the programmer can make informed judgements about the algorithms they use. Features: includes both introductory and advanced data structures and algorithms topics, with suggested chapter sequences for those respective courses provided in the preface; provides learning goals, review questions and programming exercises in each chapter, as well as numerous illustrative examples; offers downloadable programs and supplementary files at an associated website, with instructor materials available from the author; presents a primer on Python for those from a different language ...
Handbook on Data CentersThis handbook offers a comprehensive review of the state-of-the-art research achievements in the field of data centers. Contributions from international, leading researchers and scholars offer topics in cloud computing, virtualization in data centers, energy efficient data centers, and next generation data center architecture. It also comprises current research trends in emerging areas, such as data security, data protection management, and network resource management in data centers.
Specific attention is devoted to industry needs associated with the challenges faced by data centers, such as various power, cooling, floor space, and associated environmental health and safety issues, while still working to support growth without disrupting quality of service. The contributions cut across various IT data technology domains as a single source to discuss the interdependencies that need to be supported to enable a virtualized, next-generation, energy efficient, economical, and environme ...
D3.js By ExampleThis book will take you through all the concepts of D3.js starting with the most basic ones and progressively building on them in each chapter to expand your knowledge of D3.js.
Starting with obtaining D3.js and creating simple data bindings to non-graphical HTML elements, you will then master the creation of graphical elements from data. You'll discover how to combine those elements into simple visualizations such as bar, line, and scatter charts, as well as more elaborate visualizations such as network diagrams, Sankey diagrams, maps, and choreopleths.
Using practical examples provided, you will quickly get to grips with the features of D3.js and use this learning to create your own spectacular data visualizations with D3.js. ...
Practical Statistics for Data ScientistsStatistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not.
Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you're familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format.
Why exploratory data analysis is a key preliminary step in data science; How random sampling can reduce bias and yield a higher quality dataset, even with big data; How the principles of experimental design yield definitive answers to questions; How to use regression to estimate outcomes and detect anomalies; Key classification techni ...