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Mastering Gephi Network Visualization

Mastering Gephi Network Visualization Author Ken Cherven
ISBN-10 9781783987351
Release 2015-01-28
Pages 378
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This book is intended for anyone interested in advanced network analysis. If you wish to master the skills of analyzing and presenting network graphs effectively, then this is the book for you. No coding experience is required to use this book, although some familiarity with the Gephi user interface will be helpful.

Network Graph Analysis and Visualization with Gephi

Network Graph Analysis and Visualization with Gephi Author Ken Cherven
ISBN-10 9781783280148
Release 2013-09-24
Pages 116
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A practical, hands-on guide, that provides you with all the tools you need to visualize and analyze your data using network graphs with Gephi.This book is for data analysts who want to intuitively reveal patterns and trends, highlight outliers, and tell stories with their data using Gephi. It is great for anyone looking to explore interactions within network datasets, whether the data comes from social media or elsewhere. It is also a valuable resource for those seeking to learn more about Gephi without being overwhelmed by technical details.

Gephi Cookbook

Gephi Cookbook Author Devangana Khokhar
ISBN-10 9781783987412
Release 2015-05-27
Pages 296
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If you want to learn network analysis and visualization along with graph concepts from scratch, then this book is for you. This is ideal for those of you with little or no understanding of Gephi and this domain, but will also be beneficial for those interested in expanding their knowledge and experience.

Complex Network Analysis in Python

Complex Network Analysis in Python Author Dmitry Zinoviev
ISBN-10 1680502697
Release 2018-01-29
Pages 233
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Construct, analyze, and visualize networks with networkx, a Python language module. Network analysis is a powerful tool you can apply to a multitude of datasets and situations. Discover how to work with all kinds of networks, including social, product, temporal, spatial, and semantic networks. Convert almost any real-world data into a complex network--such as recommendations on co-using cosmetic products, muddy hedge fund connections, and online friendships. Analyze and visualize the network, and make business decisions based on your analysis. If you're a curious Python programmer, a data scientist, or a CNA specialist interested in mechanizing mundane tasks, you'll increase your productivity exponentially. Complex network analysis used to be done by hand or with non-programmable network analysis tools, but not anymore! You can now automate and program these tasks in Python. Complex networks are collections of connected items, words, concepts, or people. By exploring their structure and individual elements, we can learn about their meaning, evolution, and resilience. Starting with simple networks, convert real-life and synthetic network graphs into networkx data structures. Look at more sophisticated networks and learn more powerful machinery to handle centrality calculation, blockmodeling, and clique and community detection. Get familiar with presentation-quality network visualization tools, both programmable and interactive--such as Gephi, a CNA explorer. Adapt the patterns from the case studies to your problems. Explore big networks with NetworKit, a high-performance networkx substitute. Each part in the book gives you an overview of a class of networks, includes a practical study of networkx functions and techniques, and concludes with case studies from various fields, including social networking, anthropology, marketing, and sports analytics. Combine your CNA and Python programming skills to become a better network analyst, a more accomplished data scientist, and a more versatile programmer. What You Need: You will need a Python 3.x installation with the following additional modules: Pandas (>=0.18), NumPy (>=1.10), matplotlib (>=1.5), networkx (>=1.11), python-louvain (>=0.5), NetworKit (>=3.6), and generalizesimilarity. We recommend using the Anaconda distribution that comes with all these modules, except for python-louvain, NetworKit, and generalizedsimilarity, and works on all major modern operating systems.

Analyzing the Social Web

Analyzing the Social Web Author Jennifer Golbeck
ISBN-10 9780124058569
Release 2013-02-17
Pages 290
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Analyzing the Social Web provides a framework for the analysis of public data currently available and being generated by social networks and social media, like Facebook, Twitter, and Foursquare. Access and analysis of this public data about people and their connections to one another allows for new applications of traditional social network analysis techniques that let us identify things like who are the most important or influential people in a network, how things will spread through the network, and the nature of peoples' relationships. Analyzing the Social Web introduces you to these techniques, shows you their application to many different types of social media, and discusses how social media can be used as a tool for interacting with the online public. Presents interactive social applications on the web, and the types of analysis that are currently conducted in the study of social media. Covers the basics of network structures for beginners, including measuring methods for describing nodes, edges, and parts of the network. Discusses the major categories of social media applications or phenomena and shows how the techniques presented can be applied to analyze and understand the underlying data. Provides an introduction to information visualization, particularly network visualization techniques, and methods for using them to identify interesting features in a network, generate hypotheses for analysis, and recognize patterns of behavior. Includes a supporting website with lecture slides, exercises, and downloadable social network data sets that can be used can be used to apply the techniques presented in the book.

Social Network Analysis

Social Network Analysis Author John Scott
ISBN-10 9781526412256
Release 2017-02-25
Pages 248
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With a new chapter on social media, new worked examples, and better addressing the needs of the newcomer (whilst still remaining authoritative), this Fourth Edition continues to be an invaluable resource in introducing readers to the theories and techniques of social network analysis

Practical Data Analysis

Practical Data Analysis Author Hector Cuesta
ISBN-10 9781785286667
Release 2016-09-30
Pages 338
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A practical guide to obtaining, transforming, exploring, and analyzing data using Python, MongoDB, and Apache Spark About This Book Learn to use various data analysis tools and algorithms to classify, cluster, visualize, simulate, and forecast your data Apply Machine Learning algorithms to different kinds of data such as social networks, time series, and images A hands-on guide to understanding the nature of data and how to turn it into insight Who This Book Is For This book is for developers who want to implement data analysis and data-driven algorithms in a practical way. It is also suitable for those without a background in data analysis or data processing. Basic knowledge of Python programming, statistics, and linear algebra is assumed. What You Will Learn Acquire, format, and visualize your data Build an image-similarity search engine Generate meaningful visualizations anyone can understand Get started with analyzing social network graphs Find out how to implement sentiment text analysis Install data analysis tools such as Pandas, MongoDB, and Apache Spark Get to grips with Apache Spark Implement machine learning algorithms such as classification or forecasting In Detail Beyond buzzwords like Big Data or Data Science, there are a great opportunities to innovate in many businesses using data analysis to get data-driven products. Data analysis involves asking many questions about data in order to discover insights and generate value for a product or a service. This book explains the basic data algorithms without the theoretical jargon, and you'll get hands-on turning data into insights using machine learning techniques. We will perform data-driven innovation processing for several types of data such as text, Images, social network graphs, documents, and time series, showing you how to implement large data processing with MongoDB and Apache Spark. Style and approach This is a hands-on guide to data analysis and data processing. The concrete examples are explained with simple code and accessible data.

Mastering Machine Learning with Spark 2 x

Mastering Machine Learning with Spark 2 x Author Alex Tellez
ISBN-10 9781785282416
Release 2017-08-31
Pages 340
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Unlock the complexities of machine learning algorithms in Spark to generate useful data insights through this data analysis tutorial About This Book Process and analyze big data in a distributed and scalable way Write sophisticated Spark pipelines that incorporate elaborate extraction Build and use regression models to predict flight delays Who This Book Is For Are you a developer with a background in machine learning and statistics who is feeling limited by the current slow and “small data” machine learning tools? Then this is the book for you! In this book, you will create scalable machine learning applications to power a modern data-driven business using Spark. We assume that you already know the machine learning concepts and algorithms and have Spark up and running (whether on a cluster or locally) and have a basic knowledge of the various libraries contained in Spark. What You Will Learn Use Spark streams to cluster tweets online Run the PageRank algorithm to compute user influence Perform complex manipulation of DataFrames using Spark Define Spark pipelines to compose individual data transformations Utilize generated models for off-line/on-line prediction Transfer the learning from an ensemble to a simpler Neural Network Understand basic graph properties and important graph operations Use GraphFrames, an extension of DataFrames to graphs, to study graphs using an elegant query language Use K-means algorithm to cluster movie reviews dataset In Detail The purpose of machine learning is to build systems that learn from data. Being able to understand trends and patterns in complex data is critical to success; it is one of the key strategies to unlock growth in the challenging contemporary marketplace today. With the meteoric rise of machine learning, developers are now keen on finding out how can they make their Spark applications smarter. This book gives you access to transform data into actionable knowledge. The book commences by defining machine learning primitives by the MLlib and H2O libraries. You will learn how to use Binary classification to detect the Higgs Boson particle in the huge amount of data produced by CERN particle collider and classify daily health activities using ensemble Methods for Multi-Class Classification. Next, you will solve a typical regression problem involving flight delay predictions and write sophisticated Spark pipelines. You will analyze Twitter data with help of the doc2vec algorithm and K-means clustering. Finally, you will build different pattern mining models using MLlib, perform complex manipulation of DataFrames using Spark and Spark SQL, and deploy your app in a Spark streaming environment. Style and approach This book takes a practical approach to help you get to grips with using Spark for analytics and to implement machine learning algorithms. We'll teach you about advanced applications of machine learning through illustrative examples. These examples will equip you to harness the potential of machine learning, through Spark, in a variety of enterprise-grade systems.

Mining the Social Web

Mining the Social Web Author Matthew A. Russell
ISBN-10 9781449388348
Release 2011-01-21
Pages 332
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Provides information on data analysis from a vareity of social networking sites, including Facebook, Twitter, and LinkedIn.

ServiceNow Cookbook

ServiceNow Cookbook Author Ashish Rudra Srivastava
ISBN-10 9781785884139
Release 2017-02-28
Pages 376
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Over 50 practical and immediately applicable recipes to help you manage services in your enterprise environment efficiently About This Book Solve problems and challenges encountered while implementing or using ServiceNow in your organization Helps you build core administration, management, and maintenance skills to automate and orchestrate your IT environment Comes with recipes to improve the way you design and create automated workflows Who This Book Is For This book targets IT professionals and administrators who have some experience of working with ServiceNow already and are looking to solve regular or unique problems that surface when using ServiceNow. It's advisable to have a basic level of administration experience with ServiceNow. Familiarity with JavaScript is assumed. What You Will Learn Grasp the basics, such as entering and navigation, required to implement ServiceNow Perform core configuration and management tasks Use the ServiceNow plugins to manage development Build and publish custom applications for service management Design data-driven apps to connect with outside worlds by getting into Client and server scripting Configure alerts and notifications and understand e-mail troubleshooting and watermarking Build and configure reports to set up your dashboard as per the requirement Create and configure workflow activities In Detail ServiceNow is the ideal platform for you to create enterprise-level applications, giving borh requesters and fulfillers better visibility and access to a process. With this title we'll guide you through the world of ServiceNow, letting you take on the best the platform offers you with the least amount of hassle. Starting with the core configuration and management tasks, this book will help you build data-driven apps and it will also explore development best practices. You will learn to set up email notifications for users and work with the database view for reporting. Next, the book will guide you through creating various tasks from the workflow and show you how to make the most of the workflow utilities available in ServiceNow. Finally, the book will drive you through the auditing and diagnosing aspects of ServiceNow. By the end of this book, you will acquire immediately applicable skills to rectify everyday problems encountered on the ServiceNow platform. Style and approach This book follows a recipe-based problem-solution approach to address and dispel challenges faced when implementing and using ServiceNow on a regular basis.It will act as a quick solution when trying to solve specific problems without having to read an exhaustive tutorial.

Visualizing Graph Data

Visualizing Graph Data Author Corey Lanum
ISBN-10 1617293075
Release 2016-09-28
Pages 232
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Summary Visualizing Graph Data teaches you not only how to build graph data structures, but also how to create your own dynamic and interactive visualizations using a variety of tools. This book is loaded with fascinating examples and case studies to show you the real-world value of graph visualizations. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Assume you are doing a great job collecting data about your customers and products. Are you able to turn your rich data into important insight? Complex relationships in large data sets can be difficult to recognize. Visualizing these connections as graphs makes it possible to see the patterns, so you can find meaning in an otherwise over-whelming sea of facts. About the Book Visualizing Graph Data teaches you how to understand graph data, build graph data structures, and create meaningful visualizations. This engaging book gently introduces graph data visualization through fascinating examples and compelling case studies. You'll discover simple, but effective, techniques to model your data, handle big data, and depict temporal and spatial data. By the end, you'll have a conceptual foundation as well as the practical skills to explore your own data with confidence. What's Inside Techniques for creating effective visualizations Examples using the Gephi and KeyLines visualization packages Real-world case studies About the Reader No prior experience with graph data is required. About the Author Corey Lanum has decades of experience building visualization and analysis applications for companies and government agencies around the globe. Table of Contents PART 1 - GRAPH VISUALIZATION BASICS Getting to know graph visualization Case studies An introduction to Gephi and KeyLines PART 2 VISUALIZE YOUR OWN DATA Data modeling How to build graph visualizations Creating interactive visualizations How to organize a chart Big data: using graphs when there's too much data Dynamic graphs: how to show data over time Graphs on maps: the where of graph visualization

The Connected Past

The Connected Past Author Tom Brughmans
ISBN-10 9780191065385
Release 2016-03-03
Pages 240
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One of the most exciting recent developments in archaeology and history has been the adoption of new perspectives which see human societies in the past—as in the present—as made up of networks of interlinked individuals. This view of people as always connected through physical and conceptual networks along which resources, information, and disease flow, requires archaeologists and historians to use new methods to understand how these networks form, function, and change over time. The Connected Past provides a constructive methodological and theoretical critique of the growth in research applying network perspectives in archaeology and history, and considers the unique challenges presented by datasets in these disciplines, including the fragmentary and material nature of such data and the functioning and change of social processes over long timespans. An international and multidisciplinary range of scholars debate both the rationale and practicalities of applying network methodologies, addressing the merits and drawbacks of specific techniques of analysis for a range of datasets and research questions, and demonstrating their approaches with concrete case studies and detailed illustrations. As well as revealing the valuable contributions archaeologists and historians can make to network science, the volume represents a crucial step towards the development of best practice in the field, especially in exploring the interactions between social and material elements of networks, and long-term network evolution.

Data Science from Scratch

Data Science from Scratch Author Joel Grus
ISBN-10 9781491904404
Release 2015-04-14
Pages 330
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Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they’re also a good way to dive into the discipline without actually understanding data science. In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out. Get a crash course in Python Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals of machine learning Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases

Data Visualization

Data Visualization Author Andy Kirk
ISBN-10 9781849693479
Release 2012-01-01
Pages 206
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A comprehensive yet quick guide to the best approaches to designing data visualizations, with real examples and illustrative diagrams. Whatever the desired outcome ensure success by following this expert design process. This book is for anyone who has responsibility for, or is interested in trying to find innovative and effective ways to visually analyze and communicate data. There is no skill, no knowledge and no role-based pre-requisites or expectations of anyone reading this book.

Learning Qlik Sense The Official Guide

Learning Qlik   Sense  The Official Guide Author Christopher Ilacqua
ISBN-10 9781782173366
Release 2015-02-09
Pages 230
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Learning Qlik® Sense is for anyone seeking to understand and utilize the revolutionary new approach to business intelligence offered by Qlik Sense. Familiarity with the basics of business intelligence will be helpful when picking up this book, but not essential.

Social and Economic Networks

Social and Economic Networks Author Matthew O. Jackson
ISBN-10 140083399X
Release 2010-11-01
Pages 520
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Networks of relationships help determine the careers that people choose, the jobs they obtain, the products they buy, and how they vote. The many aspects of our lives that are governed by social networks make it critical to understand how they impact behavior, which network structures are likely to emerge in a society, and why we organize ourselves as we do. In Social and Economic Networks, Matthew Jackson offers a comprehensive introduction to social and economic networks, drawing on the latest findings in economics, sociology, computer science, physics, and mathematics. He provides empirical background on networks and the regularities that they exhibit, and discusses random graph-based models and strategic models of network formation. He helps readers to understand behavior in networked societies, with a detailed analysis of learning and diffusion in networks, decision making by individuals who are influenced by their social neighbors, game theory and markets on networks, and a host of related subjects. Jackson also describes the varied statistical and modeling techniques used to analyze social networks. Each chapter includes exercises to aid students in their analysis of how networks function. This book is an indispensable resource for students and researchers in economics, mathematics, physics, sociology, and business.

CoreOS Essentials

CoreOS Essentials Author Rimantas Mocevicius
ISBN-10 9781785286605
Release 2015-06-29
Pages 132
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This book will help you get up and running on using CoreOS to develop effective computing networks. You will begin with understanding the basics of CoreOS. You will then discover what etcd is and how it is used, followed by launching Docker containers with systemd and fleet. Learn how to manage clusters, read system logs, and customize with cloud-config. You will set up the deployment to production using Docker builder and a private Docker registry. You will also see how to set up and use CoreUpdate and Enterprise Registry, and get an introduction to the new App Container called rkt and the newly introduced cluster manager known as Kubernetes. This book will equip you with all the information you need to leverage the power of CoreOS and the related containers for the effective deployment of your applications.