Network Science With Python And Networkx Quick Start Guide

Author by : Edward L. Platt
Languange : en
Publisher by : Packt Publishing Ltd
Format Available : PDF, ePub, Mobi
Total Read : 35
Total Download : 630
File Size : 52,5 Mb
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Description : Manipulate and analyze network data with the power of Python and NetworkX Key Features Understand the terminology and basic concepts of network science Leverage the power of Python and NetworkX to represent data as a network Apply common techniques for working with network data of varying sizes Book Description NetworkX is a leading free and open source package used for network science with the Python programming language. NetworkX can track properties of individuals and relationships, find communities, analyze resilience, detect key network locations, and perform a wide range of important tasks. With the recent release of version 2, NetworkX has been updated to be more powerful and easy to use. If you’re a data scientist, engineer, or computational social scientist, this book will guide you in using the Python programming language to gain insights into real-world networks. Starting with the fundamentals, you’ll be introduced to the core concepts of network science, along with examples that use real-world data and Python code. This book will introduce you to theoretical concepts such as scale-free and small-world networks, centrality measures, and agent-based modeling. You’ll also be able to look for scale-free networks in real data and visualize a network using circular, directed, and shell layouts. By the end of this book, you’ll be able to choose appropriate network representations, use NetworkX to build and characterize networks, and uncover insights while working with real-world systems. What you will learn Use Python and NetworkX to analyze the properties of individuals and relationships Encode data in network nodes and edges using NetworkX Manipulate, store, and summarize data in network nodes and edges Visualize a network using circular, directed and shell layouts Find out how simulating behavior on networks can give insights into real-world problems Understand the ongoing impact of network science on society, and its ethical considerations Who this book is for If you are a programmer or data scientist who wants to manipulate and analyze network data in Python, this book is perfect for you. Although prior knowledge of network science is not necessary, some Python programming experience will help you understand the concepts covered in the book easily.


Practical Data Science With Python

Author by : Nathan George
Languange : en
Publisher by : Packt Publishing Ltd
Format Available : PDF, ePub, Mobi
Total Read : 93
Total Download : 963
File Size : 41,7 Mb
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Description : The book provides a one-stop solution for getting into data science with Python and teaches how to extract insights from data.


Geospatial Data Science Quick Start Guide

Author by : Abdishakur Hassan
Languange : en
Publisher by : Packt Publishing Ltd
Format Available : PDF, ePub, Mobi
Total Read : 45
Total Download : 866
File Size : 55,5 Mb
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Description : Discover the power of location data to build effective, intelligent data models with Geospatial ecosystems Key Features Manipulate location-based data and create intelligent geospatial data models Build effective location recommendation systems used by popular companies such as Uber A hands-on guide to help you consume spatial data and parallelize GIS operations effectively Book Description Data scientists, who have access to vast data streams, are a bit myopic when it comes to intrinsic and extrinsic location-based data and are missing out on the intelligence it can provide to their models. This book demonstrates effective techniques for using the power of data science and geospatial intelligence to build effective, intelligent data models that make use of location-based data to give useful predictions and analyses. This book begins with a quick overview of the fundamentals of location-based data and how techniques such as Exploratory Data Analysis can be applied to it. We then delve into spatial operations such as computing distances, areas, extents, centroids, buffer polygons, intersecting geometries, geocoding, and more, which adds additional context to location data. Moving ahead, you will learn how to quickly build and deploy a geo-fencing system using Python. Lastly, you will learn how to leverage geospatial analysis techniques in popular recommendation systems such as collaborative filtering and location-based recommendations, and more. By the end of the book, you will be a rockstar when it comes to performing geospatial analysis with ease. What you will learn Learn how companies now use location data Set up your Python environment and install Python geospatial packages Visualize spatial data as graphs Extract geometry from spatial data Perform spatial regression from scratch Build web applications which dynamically references geospatial data Who this book is for Data Scientists who would like to leverage location-based data and want to use location-based intelligence in their data models will find this book useful. This book is also for GIS developers who wish to incorporate data analysis in their projects. Knowledge of Python programming and some basic understanding of data analysis are all you need to get the most out of this book.


Complex Networks Their Applications Vi

Author by : Chantal Cherifi
Languange : en
Publisher by : Springer
Format Available : PDF, ePub, Mobi
Total Read : 9
Total Download : 429
File Size : 50,8 Mb
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Description : This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students and practitioners a unique update on the latest advances in theory and a multitude of applications. It presents the peer-reviewed proceedings of the VI International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2017), which took place in Lyon on November 29 – December 1, 2017. The carefully selected papers cover a wide range of theoretical topics such as network models and measures; community structure, network dynamics; diffusion, epidemics and spreading processes; resilience and control as well as all the main network applications, including social and political networks; networks in finance and economics; biological and ecological networks and technological networks.


Introduction To Computational Social Science

Author by : Claudio Cioffi-Revilla
Languange : en
Publisher by : Springer Science & Business Media
Format Available : PDF, ePub, Mobi
Total Read : 65
Total Download : 599
File Size : 48,7 Mb
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Description : This reader-friendly textbook is the first work of its kind to provide a unified Introduction to Computational Social Science (CSS). Four distinct methodological approaches are examined in detail, namely automated social information extraction, social network analysis, social complexity theory and social simulation modeling. The coverage of these approaches is supported by a discussion of the historical context, as well as by a list of texts for further reading. Features: highlights the main theories of the CSS paradigm as causal explanatory frameworks that shed new light on the nature of human and social dynamics; explains how to distinguish and analyze the different levels of analysis of social complexity using computational approaches; discusses a number of methodological tools; presents the main classes of entities, objects and relations common to the computational analysis of social complexity; examines the interdisciplinary integration of knowledge in the context of social phenomena.


Data Science Essentials In Python

Author by : Dmitry Zinoviev
Languange : en
Publisher by : Pragmatic Bookshelf
Format Available : PDF, ePub, Mobi
Total Read : 22
Total Download : 935
File Size : 48,8 Mb
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Description : Go from messy, unstructured artifacts stored in SQL and NoSQL databases to a neat, well-organized dataset with this quick reference for the busy data scientist. Understand text mining, machine learning, and network analysis; process numeric data with the NumPy and Pandas modules; describe and analyze data using statistical and network-theoretical methods; and see actual examples of data analysis at work. This one-stop solution covers the essential data science you need in Python. Data science is one of the fastest-growing disciplines in terms of academic research, student enrollment, and employment. Python, with its flexibility and scalability, is quickly overtaking the R language for data-scientific projects. Keep Python data-science concepts at your fingertips with this modular, quick reference to the tools used to acquire, clean, analyze, and store data. This one-stop solution covers essential Python, databases, network analysis, natural language processing, elements of machine learning, and visualization. Access structured and unstructured text and numeric data from local files, databases, and the Internet. Arrange, rearrange, and clean the data. Work with relational and non-relational databases, data visualization, and simple predictive analysis (regressions, clustering, and decision trees). See how typical data analysis problems are handled. And try your hand at your own solutions to a variety of medium-scale projects that are fun to work on and look good on your resume. Keep this handy quick guide at your side whether you're a student, an entry-level data science professional converting from R to Python, or a seasoned Python developer who doesn't want to memorize every function and option. What You Need: You need a decent distribution of Python 3.3 or above that includes at least NLTK, Pandas, NumPy, Matplotlib, Networkx, SciKit-Learn, and BeautifulSoup. A great distribution that meets the requirements is Anaconda, available for free from www.continuum.io. If you plan to set up your own database servers, you also need MySQL (www.mysql.com) and MongoDB (www.mongodb.com). Both packages are free and run on Windows, Linux, and Mac OS.


Web And Network Data Science

Author by : Thomas W. Miller
Languange : en
Publisher by : FT Press
Format Available : PDF, ePub, Mobi
Total Read : 70
Total Download : 550
File Size : 44,7 Mb
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Description : Master modern web and network data modeling: both theory and applications. In Web and Network Data Science, a top faculty member of Northwestern University’s prestigious analytics program presents the first fully-integrated treatment of both the business and academic elements of web and network modeling for predictive analytics. Some books in this field focus either entirely on business issues (e.g., Google Analytics and SEO); others are strictly academic (covering topics such as sociology, complexity theory, ecology, applied physics, and economics). This text gives today's managers and students what they really need: integrated coverage of concepts, principles, and theory in the context of real-world applications. Building on his pioneering Web Analytics course at Northwestern University, Thomas W. Miller covers usability testing, Web site performance, usage analysis, social media platforms, search engine optimization (SEO), and many other topics. He balances this practical coverage with accessible and up-to-date introductions to both social network analysis and network science, demonstrating how these disciplines can be used to solve real business problems.


Social Network Analysis For Startups

Author by : Maksim Tsvetovat
Languange : en
Publisher by : "O'Reilly Media, Inc."
Format Available : PDF, ePub, Mobi
Total Read : 39
Total Download : 842
File Size : 40,8 Mb
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Description : SNA techniques are derived from sociological and social-psychological theories and take into account the whole network (or, in case of very large networks such as Twitter -- a large segment of the network). Thus, we may arrive at results that may seem counter-intuitive -- e.g. that Jusin Bieber (7.5 mil. followers) and Lady Gaga (7.2 mil. followers) have relatively little actual influence despite their celebrity status -- while a middle-of-the-road blogger with 30K followers is able to generate tweets that "go viral" and result in millions of impressions. O'Reilly's "Mining Social Media" and "Programming Collective Intelligence" books are an excellent start for people inteseted in SNA. This book builds on these books' foundations to teach a new, pragmatic, way of doing SNA. I would like to write a book that links theory ("why is this important?", "how do various concepts interact?", "how do I interpret quantitative results?") and practice -- gathering, analyzing and visualizing data using Python and other open-source tools.


Python Data Science Essentials

Author by : Alberto Boschetti
Languange : en
Publisher by : Packt Publishing Ltd
Format Available : PDF, ePub, Mobi
Total Read : 58
Total Download : 455
File Size : 55,7 Mb
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Description : Python Data Science Essentials, Third Edition provides modern insight in setting up and performing data science operations effectively using the latest python tools and libraries. It builds faster governance on the most essential tasks such as data munging and pre-processing, along with all the techniques you require.


Guide To Big Data Applications

Author by : S. Srinivasan
Languange : en
Publisher by : Springer
Format Available : PDF, ePub, Mobi
Total Read : 70
Total Download : 109
File Size : 52,8 Mb
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Description : This handbook brings together a variety of approaches to the uses of big data in multiple fields, primarily science, medicine, and business. This single resource features contributions from researchers around the world from a variety of fields, where they share their findings and experience. This book is intended to help spur further innovation in big data. The research is presented in a way that allows readers, regardless of their field of study, to learn from how applications have proven successful and how similar applications could be used in their own field. Contributions stem from researchers in fields such as physics, biology, energy, healthcare, and business. The contributors also discuss important topics such as fraud detection, privacy implications, legal perspectives, and ethical handling of big data.


Big Data And Social Science

Author by : Ian Foster
Languange : en
Publisher by : CRC Press
Format Available : PDF, ePub, Mobi
Total Read : 76
Total Download : 807
File Size : 42,9 Mb
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Description : Both Traditional Students and Working Professionals Acquire the Skills to Analyze Social Problems. Big Data and Social Science: A Practical Guide to Methods and Tools shows how to apply data science to real-world problems in both research and the practice. The book provides practical guidance on combining methods and tools from computer science, statistics, and social science. This concrete approach is illustrated throughout using an important national problem, the quantitative study of innovation. The text draws on the expertise of prominent leaders in statistics, the social sciences, data science, and computer science to teach students how to use modern social science research principles as well as the best analytical and computational tools. It uses a real-world challenge to introduce how these tools are used to identify and capture appropriate data, apply data science models and tools to that data, and recognize and respond to data errors and limitations. For more information, including sample chapters and news, please visit the author's website.


The Sage Handbook Of Social Network Analysis

Author by : John Scott
Languange : en
Publisher by : SAGE
Format Available : PDF, ePub, Mobi
Total Read : 69
Total Download : 276
File Size : 48,5 Mb
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Description : This sparkling Handbook offers an unrivalled resource for those engaged in the cutting edge field of social network analysis. Systematically, it introduces readers to the key concepts, substantive topics, central methods and prime debates. Among the specific areas covered are: Network theory Interdisciplinary applications Online networks Corporate networks Lobbying networks Deviant networks Measuring devices Key Methodologies Software applications. The result is a peerless resource for teachers and students which offers a critical survey of the origins, basic issues and major debates. The Handbook provides a one-stop guide that will be used by readers for decades to come.


Practical Data Science

Author by : Andreas François Vermeulen
Languange : en
Publisher by : Apress
Format Available : PDF, ePub, Mobi
Total Read : 40
Total Download : 765
File Size : 50,9 Mb
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Description : Learn how to build a data science technology stack and perform good data science with repeatable methods. You will learn how to turn data lakes into business assets. The data science technology stack demonstrated in Practical Data Science is built from components in general use in the industry. Data scientist Andreas Vermeulen demonstrates in detail how to build and provision a technology stack to yield repeatable results. He shows you how to apply practical methods to extract actionable business knowledge from data lakes consisting of data from a polyglot of data types and dimensions. What You'll Learn Become fluent in the essential concepts and terminology of data science and data engineering Build and use a technology stack that meets industry criteria Master the methods for retrieving actionable business knowledge Coordinate the handling of polyglot data types in a data lake for repeatable results Who This Book Is For Data scientists and data engineers who are required to convert data from a data lake into actionable knowledge for their business, and students who aspire to be data scientists and data engineers


Complex Networks And Their Applications Viii

Author by : Hocine Cherifi
Languange : en
Publisher by : Springer Nature
Format Available : PDF, ePub, Mobi
Total Read : 25
Total Download : 235
File Size : 49,9 Mb
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Description : This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students, and practitioners a unique update on the latest advances in theory and a multitude of applications. It presents the peer-reviewed proceedings of the Eighth International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2019), which took place in Lisbon, Portugal, on December 10–12, 2019. The carefully selected papers cover a wide range of theoretical topics such as network models and measures; community structure, and network dynamics; diffusion, epidemics, and spreading processes; resilience and control as well as all the main network applications, including social and political networks; networks in finance and economics; biological and neuroscience networks; and technological networks.


Encyclopedia Of Bioinformatics And Computational Biology

Author by : Anonim
Languange : en
Publisher by : Elsevier
Format Available : PDF, ePub, Mobi
Total Read : 21
Total Download : 146
File Size : 50,5 Mb
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Description : Encyclopedia of Bioinformatics and Computational Biology: ABC of Bioinformatics combines elements of computer science, information technology, mathematics, statistics and biotechnology, providing the methodology and in silico solutions to mine biological data and processes. The book covers Theory, Topics and Applications, with a special focus on Integrative –omics and Systems Biology. The theoretical, methodological underpinnings of BCB, including phylogeny are covered, as are more current areas of focus, such as translational bioinformatics, cheminformatics, and environmental informatics. Finally, Applications provide guidance for commonly asked questions. This major reference work spans basic and cutting-edge methodologies authored by leaders in the field, providing an invaluable resource for students, scientists, professionals in research institutes, and a broad swath of researchers in biotechnology and the biomedical and pharmaceutical industries. Brings together information from computer science, information technology, mathematics, statistics and biotechnology Written and reviewed by leading experts in the field, providing a unique and authoritative resource Focuses on the main theoretical and methodological concepts before expanding on specific topics and applications Includes interactive images, multimedia tools and crosslinking to further resources and databases


Python Data Analysis Cookbook

Author by : Ivan Idris
Languange : en
Publisher by : Packt Publishing Ltd
Format Available : PDF, ePub, Mobi
Total Read : 12
Total Download : 425
File Size : 43,7 Mb
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Description : Over 140 practical recipes to help you make sense of your data with ease and build production-ready data apps About This Book Analyze Big Data sets, create attractive visualizations, and manipulate and process various data types Packed with rich recipes to help you learn and explore amazing algorithms for statistics and machine learning Authored by Ivan Idris, expert in python programming and proud author of eight highly reviewed books Who This Book Is For This book teaches Python data analysis at an intermediate level with the goal of transforming you from journeyman to master. Basic Python and data analysis skills and affinity are assumed. What You Will Learn Set up reproducible data analysis Clean and transform data Apply advanced statistical analysis Create attractive data visualizations Web scrape and work with databases, Hadoop, and Spark Analyze images and time series data Mine text and analyze social networks Use machine learning and evaluate the results Take advantage of parallelism and concurrency In Detail Data analysis is a rapidly evolving field and Python is a multi-paradigm programming language suitable for object-oriented application development and functional design patterns. As Python offers a range of tools and libraries for all purposes, it has slowly evolved as the primary language for data science, including topics on: data analysis, visualization, and machine learning. Python Data Analysis Cookbook focuses on reproducibility and creating production-ready systems. You will start with recipes that set the foundation for data analysis with libraries such as matplotlib, NumPy, and pandas. You will learn to create visualizations by choosing color maps and palettes then dive into statistical data analysis using distribution algorithms and correlations. You'll then help you find your way around different data and numerical problems, get to grips with Spark and HDFS, and then set up migration scripts for web mining. In this book, you will dive deeper into recipes on spectral analysis, smoothing, and bootstrapping methods. Moving on, you will learn to rank stocks and check market efficiency, then work with metrics and clusters. You will achieve parallelism to improve system performance by using multiple threads and speeding up your code. By the end of the book, you will be capable of handling various data analysis techniques in Python and devising solutions for problem scenarios. Style and Approach The book is written in “cookbook” style striving for high realism in data analysis. Through the recipe-based format, you can read each recipe separately as required and immediately apply the knowledge gained.


Practical Data Science Cookbook

Author by : Prabhanjan Tattar
Languange : en
Publisher by : Packt Publishing Ltd
Format Available : PDF, ePub, Mobi
Total Read : 53
Total Download : 584
File Size : 50,8 Mb
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Description : Over 85 recipes to help you complete real-world data science projects in R and Python About This Book Tackle every step in the data science pipeline and use it to acquire, clean, analyze, and visualize your data Get beyond the theory and implement real-world projects in data science using R and Python Easy-to-follow recipes will help you understand and implement the numerical computing concepts Who This Book Is For If you are an aspiring data scientist who wants to learn data science and numerical programming concepts through hands-on, real-world project examples, this is the book for you. Whether you are brand new to data science or you are a seasoned expert, you will benefit from learning about the structure of real-world data science projects and the programming examples in R and Python. What You Will Learn Learn and understand the installation procedure and environment required for R and Python on various platforms Prepare data for analysis by implement various data science concepts such as acquisition, cleaning and munging through R and Python Build a predictive model and an exploratory model Analyze the results of your model and create reports on the acquired data Build various tree-based methods and Build random forest In Detail As increasing amounts of data are generated each year, the need to analyze and create value out of it is more important than ever. Companies that know what to do with their data and how to do it well will have a competitive advantage over companies that don't. Because of this, there will be an increasing demand for people that possess both the analytical and technical abilities to extract valuable insights from data and create valuable solutions that put those insights to use. Starting with the basics, this book covers how to set up your numerical programming environment, introduces you to the data science pipeline, and guides you through several data projects in a step-by-step format. By sequentially working through the steps in each chapter, you will quickly familiarize yourself with the process and learn how to apply it to a variety of situations with examples using the two most popular programming languages for data analysis—R and Python. Style and approach This step-by-step guide to data science is full of hands-on examples of real-world data science tasks. Each recipe focuses on a particular task involved in the data science pipeline, ranging from readying the dataset to analytics and visualization


A Librarian S Guide To Graphs Data And The Semantic Web

Author by : James Powell
Languange : en
Publisher by : Elsevier
Format Available : PDF, ePub, Mobi
Total Read : 99
Total Download : 692
File Size : 50,7 Mb
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Description : Graphs are about connections, and are an important part of our connected and data-driven world. A Librarian's Guide to Graphs, Data and the Semantic Web is geared toward library and information science professionals, including librarians, software developers and information systems architects who want to understand the fundamentals of graph theory, how it is used to represent and explore data, and how it relates to the semantic web. This title provides a firm grounding in the field at a level suitable for a broad audience, with an emphasis on open source solutions and what problems these tools solve at a conceptual level, with minimal emphasis on algorithms or mathematics. The text will also be of special interest to data science librarians and data professionals, since it introduces many graph theory concepts by exploring data-driven networks from various scientific disciplines. The first two chapters consider graphs in theory and the science of networks, before the following chapters cover networks in various disciplines. Remaining chapters move on to library networks, graph tools, graph analysis libraries, information problems and network solutions, and semantic graphs and the semantic web. Provides an accessible introduction to network science that is suitable for a broad audience Devotes several chapters to a survey of how graph theory has been used in a number of scientific data-driven disciplines Explores how graph theory could aid library and information scientists


Computation In Complex Networks

Author by : Clara Pizzuti
Languange : en
Publisher by : MDPI
Format Available : PDF, ePub, Mobi
Total Read : 35
Total Download : 782
File Size : 50,7 Mb
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Description : Complex networks are one of the most challenging research focuses of disciplines, including physics, mathematics, biology, medicine, engineering, and computer science, among others. The interest in complex networks is increasingly growing, due to their ability to model several daily life systems, such as technology networks, the Internet, and communication, chemical, neural, social, political and financial networks. The Special Issue “Computation in Complex Networks" of Entropy offers a multidisciplinary view on how some complex systems behave, providing a collection of original and high-quality papers within the research fields of: • Community detection • Complex network modelling • Complex network analysis • Node classification • Information spreading and control • Network robustness • Social networks • Network medicine


Statistics Data Mining And Machine Learning In Astronomy

Author by : Željko Ivezić
Languange : en
Publisher by : Princeton University Press
Format Available : PDF, ePub, Mobi
Total Read : 53
Total Download : 485
File Size : 43,6 Mb
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Description : As telescopes, detectors, and computers grow ever more powerful, the volume of data at the disposal of astronomers and astrophysicists will enter the petabyte domain, providing accurate measurements for billions of celestial objects. This book provides a comprehensive and accessible introduction to the cutting-edge statistical methods needed to efficiently analyze complex data sets from astronomical surveys such as the Panoramic Survey Telescope and Rapid Response System, the Dark Energy Survey, and the upcoming Large Synoptic Survey Telescope. It serves as a practical handbook for graduate students and advanced undergraduates in physics and astronomy, and as an indispensable reference for researchers. Statistics, Data Mining, and Machine Learning in Astronomy presents a wealth of practical analysis problems, evaluates techniques for solving them, and explains how to use various approaches for different types and sizes of data sets. For all applications described in the book, Python code and example data sets are provided. The supporting data sets have been carefully selected from contemporary astronomical surveys (for example, the Sloan Digital Sky Survey) and are easy to download and use. The accompanying Python code is publicly available, well documented, and follows uniform coding standards. Together, the data sets and code enable readers to reproduce all the figures and examples, evaluate the methods, and adapt them to their own fields of interest. Describes the most useful statistical and data-mining methods for extracting knowledge from huge and complex astronomical data sets Features real-world data sets from contemporary astronomical surveys Uses a freely available Python codebase throughout Ideal for students and working astronomers


Practical Design Of Ships And Other Floating Structures

Author by : Tetsuo Okada
Languange : en
Publisher by : Springer Nature
Format Available : PDF, ePub, Mobi
Total Read : 42
Total Download : 266
File Size : 54,7 Mb
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Description : This book gathers the peer-reviewed proceedings of the 14th International Symposium, PRADS 2019, held in Yokohama, Japan, in September 2019. It brings together naval architects, engineers, academic researchers and professionals who are involved in ships and other floating structures to share the latest research advances in the field. The contents cover a broad range of topics, including design synthesis for ships and floating systems, production, hydrodynamics, and structures and materials. Reflecting the latest advances, the book will be of interest to researchers and practitioners alike.


Malware Analysis Using Artificial Intelligence And Deep Learning

Author by : Mark Stamp
Languange : en
Publisher by : Springer Nature
Format Available : PDF, ePub, Mobi
Total Read : 42
Total Download : 462
File Size : 47,7 Mb
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Description : ​This book is focused on the use of deep learning (DL) and artificial intelligence (AI) as tools to advance the fields of malware detection and analysis. The individual chapters of the book deal with a wide variety of state-of-the-art AI and DL techniques, which are applied to a number of challenging malware-related problems. DL and AI based approaches to malware detection and analysis are largely data driven and hence minimal expert domain knowledge of malware is needed. This book fills a gap between the emerging fields of DL/AI and malware analysis. It covers a broad range of modern and practical DL and AI techniques, including frameworks and development tools enabling the audience to innovate with cutting-edge research advancements in a multitude of malware (and closely related) use cases.


Proceedings Of Sixth International Congress On Information And Communication Technology

Author by : Xin-She Yang
Languange : en
Publisher by : Springer Nature
Format Available : PDF, ePub, Mobi
Total Read : 26
Total Download : 205
File Size : 41,7 Mb
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Description : This book gathers selected high-quality research papers presented at the Sixth International Congress on Information and Communication Technology, held at Brunel University, London, on February 25–26, 2021. It discusses emerging topics pertaining to information and communication technology (ICT) for managerial applications, e-governance, e-agriculture, e-education and computing technologies, the Internet of things (IoT) and e-mining. Written by respected experts and researchers working on ICT, the book offers a valuable asset for young researchers involved in advanced studies. The book is presented in four volumes.


Comparative Genomics

Author by : Mathieu Blanchette
Languange : en
Publisher by : Springer
Format Available : PDF, ePub, Mobi
Total Read : 45
Total Download : 898
File Size : 54,8 Mb
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Description : This book constitutes the proceedings of the 16th International Conference on Comparative Genomics, RECOMB-CG 2018, held in Magog-Orford, QC, Canada, in October 2018. The 18 full papers presented were carefully reviewed and selected from 29 submissions. The papers cover topics such as: genome rearrangements; genome sequencing; applied comparative genomics; reconciliation and coalescence; and phylogenetics.


Mathematical Models For The Design Of Electrical Machines

Author by : Frédéric Dubas
Languange : en
Publisher by : MDPI
Format Available : PDF, ePub, Mobi
Total Read : 93
Total Download : 820
File Size : 44,5 Mb
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Description : This book is a comprehensive set of articles reflecting the latest advances and developments in mathematical modeling and the design of electrical machines for different applications. The main models discussed are based on the: i) Maxwell–Fourier method (i.e., the formal resolution of Maxwell’s equations by using the separation of variables method and the Fourier’s series in 2-D or 3-D with a quasi-Cartesian or polar coordinate system); ii) electrical, thermal and magnetic equivalent circuit; iii) hybrid model. In these different papers, the numerical method and the experimental tests have been used as comparisons or validations.


Archeologia E Calcolatori 30 2019

Author by : Marco Arizza
Languange : en
Publisher by : All’Insegna del Giglio
Format Available : PDF, ePub, Mobi
Total Read : 72
Total Download : 375
File Size : 53,5 Mb
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Description : Il volume 30 di «Archeologia e Calcolatori» si apre con un inserto speciale, dedicato al trentennale della rivista. Alle introduzioni di F. Djindjian e di P. Moscati, che delineano un quadro dell’informatica archeologica nel suo divenire, seguono gli articoli dei membri del Comitato di Redazione, a testimoniare l’attività di ricerca e di sperimentazione che ha caratterizzato il cammino editoriale della rivista, e il contributo di una giovane laureata dell’Università Bocconi, che ha lavorato a stretto contatto con il team di «Archeologia e Calcolatori». Nella parte centrale sono pubblicati gli articoli proposti annualmente dagli autori. Ne emerge un quadro che rappresenta gli aspetti applicativi più qualificanti dell’informatica archeologica (le banche dati, i GIS, le analisi statistiche, i sistemi multimediali), ma che guarda oggi con sempre maggiore interesse agli strumenti di visualizzazione scientifica e di comunicazione delle conoscenze. Il volume si chiude con gli Atti del XII Workshop ArcheoFOSS (Free, Libre and Open Source Software e Open Format nei processi di ricerca archeologica), un’iniziativa lodevole, nata nel 2006, cui si è più volte dato spazio nelle pagine della rivista.


Information Security

Author by : Xuejia Lai
Languange : en
Publisher by : Springer Science & Business Media
Format Available : PDF, ePub, Mobi
Total Read : 39
Total Download : 137
File Size : 48,8 Mb
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Description : This book constitutes the refereed proceedings of the 14th International Conference on Information Security, ISC 2011, held in Xi'an, China, in October 2011. The 25 revised full papers were carefully reviewed and selected from 95 submissions. The papers are organized in topical sections on attacks; protocols; public-key cryptosystems; network security; software security; system security; database security; privacy; digital signatures.


Guide To Programming For The Digital Humanities

Author by : Brian Kokensparger
Languange : en
Publisher by : Springer
Format Available : PDF, ePub, Mobi
Total Read : 49
Total Download : 997
File Size : 46,6 Mb
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Description : As an introduction to programming for the Digital Humanities (DH), this book presents six key assignments oriented on DH topics. The topics include Computing Change Over Time (calculating burials at a historic cemetery), Visualizing Change Over Time (visualizing the burials at the historic cemetery), Textual Analysis (finding word frequencies and “stop words” in public domain texts), XML Transformation (transforming a simplified version of XML into HTML styled with CSS), Stylometry (comparing the measured features of graphic images), and Social Network Analysis (analyzing extended relationships in historic circles). The book focuses on the practical application of these assignments in the classroom, providing a range of variations for each assignment, which can be selected on the basis of students’ specific programming background and skills; “atomic” assignments, which can be used to give students the experience they need to successfully complete the main assignments; and some common pitfalls and gotchas to manage in the classroom. The book’s chief goals are to introduce novice computer science (CS) students to programming for DH, and to offer them valuable hands-on experience with core programming concepts.


Social Media Mining With Python

Author by : Debanjan Mahata
Languange : en
Publisher by : Unknown
Format Available : PDF, ePub, Mobi
Total Read : 51
Total Download : 456
File Size : 54,8 Mb
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Description : Leverage the power of social media to gain insight into global trends using PythonAbout This Book* Learn to use APIs for popular social media websites and collect data from Twitter, Facebook, Pinterest, Instagram, Foursquare, LinkedIn, and Reddit* Perform sentiment analysis using the readily available machine learning and basic deep learning Python libraries to extract valuable information from short social media text* This hands-on guide is packed with practical, real-life examples to help you implement social media miningWho This Book Is ForIf you are a Python programmer who wants to understand the details of social media websites' APIs, or a social science major or data scientist who wants work with social media, then this book is for you. A basic Python programming knowledge is sufficient for you to get going.What You Will Learn* Learn the techniques to effectively analyze large volumes of social media data* Make RESTful calls to API services of different social media websites and authenticate clients using OAuth* Work with the Natural Language Toolkit, Sklearn, NetworkX, Pandas, and other popular Python libraries* Perform sentiment analysis of social media text* Leverage Spark to collect, process, and analyze social media data* Store and read data from cloud storage such as DynamoDB and S3* Utilize Python visualization libraries to gain more insights and visualize dataIn DetailMillions of Internet users take to social networks to discuss and review products, provide opinions, and express their viewpoints on various topics. Social media mining helps with the extraction and discovery of information from huge amounts of data produced on social media websites. It also aids in the process of making data-driven decisions by drawing actionable insights from social data. This process can be automated using Python to save time and costs.The book will get you started and get you ready to explore and mine the wide horizon of social media data along with its nuances. It starts by giving you an overview of social media mining and the challenges involved. You will learn about standard authentication techniques to query social media websites. You will also see how to work with the LinkedIn and Facebook APIs and collect and analyze data using various tools. Moving on, you will find out how to collect data related to a social media campaign from YouTube and analyze it. Then, you will discover how to perform sentiment analysis on Twitter and crawl blogs.Finally, you will be introduced to various cloud services and storage options for big data.By the end of this book, you will be able to use Python to extract meaningful information and insights from large datasets found on social media websites such as Twitter, Facebook, and blogs.


Practical Data Analysis Cookbook

Author by : Tomasz Drabas
Languange : en
Publisher by : Packt Publishing Ltd
Format Available : PDF, ePub, Mobi
Total Read : 81
Total Download : 826
File Size : 44,8 Mb
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Description : Over 60 practical recipes on data exploration and analysis About This Book Clean dirty data, extract accurate information, and explore the relationships between variables Forecast the output of an electric plant and the water flow of American rivers using pandas, NumPy, Statsmodels, and scikit-learn Find and extract the most important features from your dataset using the most efficient Python libraries Who This Book Is For If you are a beginner or intermediate-level professional who is looking to solve your day-to-day, analytical problems with Python, this book is for you. Even with no prior programming and data analytics experience, you will be able to finish each recipe and learn while doing so. What You Will Learn Read, clean, transform, and store your data usng Pandas and OpenRefine Understand your data and explore the relationships between variables using Pandas and D3.js Explore a variety of techniques to classify and cluster outbound marketing campaign calls data of a bank using Pandas, mlpy, NumPy, and Statsmodels Reduce the dimensionality of your dataset and extract the most important features with pandas, NumPy, and mlpy Predict the output of a power plant with regression models and forecast water flow of American rivers with time series methods using pandas, NumPy, Statsmodels, and scikit-learn Explore social interactions and identify fraudulent activities with graph theory concepts using NetworkX and Gephi Scrape Internet web pages using urlib and BeautifulSoup and get to know natural language processing techniques to classify movies ratings using NLTK Study simulation techniques in an example of a gas station with agent-based modeling In Detail Data analysis is the process of systematically applying statistical and logical techniques to describe and illustrate, condense and recap, and evaluate data. Its importance has been most visible in the sector of information and communication technologies. It is an employee asset in almost all economy sectors. This book provides a rich set of independent recipes that dive into the world of data analytics and modeling using a variety of approaches, tools, and algorithms. You will learn the basics of data handling and modeling, and will build your skills gradually toward more advanced topics such as simulations, raw text processing, social interactions analysis, and more. First, you will learn some easy-to-follow practical techniques on how to read, write, clean, reformat, explore, and understand your data—arguably the most time-consuming (and the most important) tasks for any data scientist. In the second section, different independent recipes delve into intermediate topics such as classification, clustering, predicting, and more. With the help of these easy-to-follow recipes, you will also learn techniques that can easily be expanded to solve other real-life problems such as building recommendation engines or predictive models. In the third section, you will explore more advanced topics: from the field of graph theory through natural language processing, discrete choice modeling to simulations. You will also get to expand your knowledge on identifying fraud origin with the help of a graph, scrape Internet websites, and classify movies based on their reviews. By the end of this book, you will be able to efficiently use the vast array of tools that the Python environment has to offer. Style and approach This hands-on recipe guide is divided into three sections that tackle and overcome real-world data modeling problems faced by data analysts/scientist in their everyday work. Each independent recipe is written in an easy-to-follow and step-by-step fashion.