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Author: Ken Cherven
Publisher: Packt Publishing Ltd
ISBN: 1783987359
Category : Computers
Languages : en
Pages : 378
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Book Description
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.
Author: Ken Cherven
Publisher: Packt Publishing Ltd
ISBN: 1783987359
Category : Computers
Languages : en
Pages : 378
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Book Description
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.
Author: Devangana Khokhar
Publisher: Packt Publishing Ltd
ISBN: 1783987413
Category : Computers
Languages : en
Pages : 296
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Book Description
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.
Author: Dmitry Zinoviev
Publisher: Pragmatic Bookshelf
ISBN: 1680505408
Category : Computers
Languages : en
Pages : 330
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Book Description
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.
Author: Simon R. Chapple
Publisher: Packt Publishing Ltd
ISBN: 1784394629
Category : Computers
Languages : en
Pages : 244
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Book Description
Master the robust features of R parallel programming to accelerate your data science computations About This Book Create R programs that exploit the computational capability of your cloud platforms and computers to the fullest Become an expert in writing the most efficient and highest performance parallel algorithms in R Get to grips with the concept of parallelism to accelerate your existing R programs Who This Book Is For This book is for R programmers who want to step beyond its inherent single-threaded and restricted memory limitations and learn how to implement highly accelerated and scalable algorithms that are a necessity for the performant processing of Big Data. No previous knowledge of parallelism is required. This book also provides for the more advanced technical programmer seeking to go beyond high level parallel frameworks. What You Will Learn Create and structure efficient load-balanced parallel computation in R, using R's built-in parallel package Deploy and utilize cloud-based parallel infrastructure from R, including launching a distributed computation on Hadoop running on Amazon Web Services (AWS) Get accustomed to parallel efficiency, and apply simple techniques to benchmark, measure speed and target improvement in your own code Develop complex parallel processing algorithms with the standard Message Passing Interface (MPI) using RMPI, pbdMPI, and SPRINT packages Build and extend a parallel R package (SPRINT) with your own MPI-based routines Implement accelerated numerical functions in R utilizing the vector processing capability of your Graphics Processing Unit (GPU) with OpenCL Understand parallel programming pitfalls, such as deadlock and numerical instability, and the approaches to handle and avoid them Build a task farm master-worker, spatial grid, and hybrid parallel R programs In Detail R is one of the most popular programming languages used in data science. Applying R to big data and complex analytic tasks requires the harnessing of scalable compute resources. Mastering Parallel Programming with R presents a comprehensive and practical treatise on how to build highly scalable and efficient algorithms in R. It will teach you a variety of parallelization techniques, from simple use of R's built-in parallel package versions of lapply(), to high-level AWS cloud-based Hadoop and Apache Spark frameworks. It will also teach you low level scalable parallel programming using RMPI and pbdMPI for message passing, applicable to clusters and supercomputers, and how to exploit thousand-fold simple processor GPUs through ROpenCL. By the end of the book, you will understand the factors that influence parallel efficiency, including assessing code performance and implementing load balancing; pitfalls to avoid, including deadlock and numerical instability issues; how to structure your code and data for the most appropriate type of parallelism for your problem domain; and how to extract the maximum performance from your R code running on a variety of computer systems. Style and approach This book leads you chapter by chapter from the easy to more complex forms of parallelism. The author's insights are presented through clear practical examples applied to a range of different problems, with comprehensive reference information for each of the R packages employed. The book can be read from start to finish, or by dipping in chapter by chapter, as each chapter describes a specific parallel approach and technology, so can be read as a standalone.
Author: Ken Cherven
Publisher: Packt Pub Limited
ISBN: 9781783280131
Category : COMPUTERS
Languages : en
Pages : 116
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Book Description
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.
Author: Patrick J. Driscoll
Publisher: John Wiley & Sons
ISBN: 1119901421
Category : Computers
Languages : en
Pages : 580
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Book Description
DECISION MAKING IN SYSTEMS ENGINEERING AND MANAGEMENT A thoroughly updated overview of systems engineering management and decision making In the newly revised third edition of Decision Making in Systems Engineering and Management, the authors deliver a comprehensive and authoritative overview of the systems decision process, systems thinking, and qualitative and quantitative multi-criteria value modeling directly supporting decision making throughout the system lifecycle. This book offers readers major new updates that cover recently developed system modeling and analysis techniques and quantitative and qualitative approaches in the field, including effective techniques for addressing uncertainty. In addition to Excel, six new open-source software applications have been added to illustrate key topics, including SIPmath Modeler Tools, Cambridge Advanced Modeller, SystemiTool2.0, and Gephi 0.9.2. The authors have reshaped the book’s organization and presentation to better support educators engaged in remote learning. New appendices have been added to present extensions for a new realization analysis technique and getting started steps for each of the major software applications. Updated illustrative examples support modern system decision making skills and highlight applications in hardware, organizations, policy, logistic supply chains, and architecture. Readers will also find: Thorough introductions to working with systems, the systems engineering perspective, and systems thinking In-depth presentations of applied systems thinking, including holism, element dependencies, expansive and contractive thinking, and concepts of structure, classification, and boundaries Comprehensive explorations of system representations leading to analysis In-depth discussions of supporting system decisions, including the system decision process (SDP), tradespace methods, multi-criteria value modeling, working with stakeholders, and the system environment Perfect for undergraduate and graduate students studying systems engineering and systems engineering management, Decision Making in Systems Engineering and Management will also earn a place in the libraries of practicing system engineers and researchers with an interest in the topic.
Author: Mehmet Hüseyin Bilgin
Publisher: Springer Nature
ISBN: 3031362861
Category : Business & Economics
Languages : en
Pages : 400
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Book Description
EBES conferences have been an intellectual hub for academic discussion in economics, finance, and business fields and provide network opportunities for participants to make long-lasting academic cooperation. This is the 26th volume of the Eurasian Studies in Business and Economics (EBES’s official proceeding series), which includes selected papers from the 38th EBES Conference which took place in Warsaw. The conference was organized in hybrid mode with both online and in-person presentations at the Faculty of Economics Sciences, the University of Warsaw in Warsaw, Poland, on January 12-14, 2022. At the conference, 197 papers by 439 colleagues from 50 countries were presented. Both theoretical and empirical papers in this volume cover diverse areas of business, economics, and finance from many different regions.
Author: Florentina Armaselu
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3111317773
Category : History
Languages : en
Pages : 490
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Book Description
Despite a variety of theoretical and practical undertakings, there is no coherent understanding of the concept of scale in digital history and humanities, and its potential is largely unexplored. A clearer picture of the whole spectrum is needed, from large to small, distant to close, global to local, general to specific, macro to micro, and the in-between levels. The book addresses these issues and sketches out the territory of Zoomland, at scale. Four regions and sixteen chapters are conceptually and symbolically depicted through three perspectives: bird's eye, overhead, and ground view. The variable-scale representation allows for exploratory paths covering areas such as: theoretical and applicative reflections on scale combining a digital dimension with research in history, media studies, cultural heritage, literature, text analysis, and map modelling; creative use of scale in new digital forms of analysis, data organisation, interfaces, and argumentative or artistic expressions. Zoomland provides a systematic discussion on the epistemological dimensions, hermeneutic methods, empirical tools, and aesthetic logic pertaining to scale and its innovative possibilities residing in humanities-based approaches and digital technologies.
Author: Cybellium Ltd
Publisher: Cybellium Ltd
ISBN:
Category : Computers
Languages : en
Pages : 207
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Book Description
Communicate Insights Through Compelling Visuals Are you prepared to transform your data into compelling visual stories? "Mastering Data Visualization" is your ultimate guide to unlocking the power of data visualization for effective communication of insights. Whether you're a data analyst aiming to convey findings or a business leader seeking to make data-driven decisions, this book equips you with the knowledge and techniques to master the art of data visualization. Key Features: 1. Dive into Data Visualization: Immerse yourself in the world of data visualization, understanding its significance, principles, and applications. Build a solid foundation that empowers you to convey complex information through captivating visuals. 2. Data Exploration and Preparation: Master the art of data exploration and preparation for visualization. Learn how to clean, transform, and structure data to ensure accuracy in your visual representations. 3. Visual Design Principles: Delve into visual design principles for effective communication. Explore color theory, typography, and layout techniques that enhance the clarity and impact of your visuals. 4. Charts and Graphs: Uncover a range of charts and graphs for different data types. Learn how to choose the right visualization type, from bar charts to scatter plots, to convey specific insights. 5. Interactive Visualizations: Discover the power of interactive visualizations. Learn how to create dynamic and engaging visuals that allow users to explore data on their terms. 6. Geospatial and Network Visualizations: Master geospatial and network visualizations. Explore techniques for mapping spatial data and representing relationships in complex networks. 7. Storytelling with Data: Explore the art of storytelling with data. Learn how to structure your visual narrative, build a compelling story arc, and guide viewers through your insights. 8. Visualization Tools and Software: Uncover a range of visualization tools and software. Learn how to use popular tools to create stunning visualizations and infographics. 9. Data Visualization Best Practices: Delve into best practices for creating effective data visualizations. Learn how to avoid common pitfalls, ensure accessibility, and tailor visuals to your audience. 10. Real-World Applications: Gain insights into real-world use cases of data visualization across industries. From business reports to interactive dashboards, discover how organizations leverage data visualization for impactful communication. Who This Book Is For: "Mastering Data Visualization" is an essential resource for data analysts, designers, and business professionals aiming to excel in conveying insights through visual storytelling. Whether you're enhancing your technical skills or transforming data into actionable insights, this book will guide you through the intricacies and empower you to harness the full potential of data visualization. © 2023 Cybellium Ltd. All rights reserved. www.cybellium.com
Author: Ashley R. Sanders
Publisher: Springer Nature
ISBN: 3031469763
Category :
Languages : en
Pages : 367
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Book Description
