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Social Computing and Virtual Communities

Social Computing and Virtual Communities

Growing more quickly than we can study or come to fully understand it social computing is much more than the next thing. Whether it is due more to technology-driven convenience or to the basic human need to find kindred connection online communication and communities are changing the way we live. Social Computing and Virtual Communities compiles contributions from international experts to offer the sort of multidisciplinary study that is required in any investigation of communities. Delving fully into theories and methods application areas and types of online social environments this book — Introduces several theories regarding online social interaction Provides a general overview of methodologies qualitative and quantitative for analyzing and evaluating virtual communities Makes an in-depth investigation into e-learning communities and the formation of social networks of learners Examines healthcare communities motivated by physical pain illness and burdensome symptoms Discusses intellectual property (IP) issues including those involving user-generated content Delves into the topic of online trust Introduces virtual communities in which users immerse themselves in a 3D virtual environment including MMORPG (massively multiplayer online role playing games) Presents an unusual community of older people of Chinese culture who perceive virtual communities as a place where old beliefs and traditional norms can be preserved Explores the rapid rise of social networking sites (SNS) Books of this kind are uncommon. This work not only provides case studies of different domains of virtual communities and different types of social technologies but also emphasizes theoretical and methodological aspects required to research and analyze such communities.

GBP 69.99
1

Introduction to Probability Second Edition

Introduction to Probability Second Edition

Developed from celebrated Harvard statistics lectures Introduction to Probability provides essential language and tools for understanding statistics randomness and uncertainty. The book explores a wide variety of applications and examples ranging from coincidences and paradoxes to Google PageRank and Markov chain Monte Carlo (MCMC). Additional application areas explored include genetics medicine computer science and information theory. The authors present the material in an accessible style and motivate concepts using real-world examples. Throughout they use stories to uncover connections between the fundamental distributions in statistics and conditioning to reduce complicated problems to manageable pieces. The book includes many intuitive explanations diagrams and practice problems. Each chapter ends with a section showing how to perform relevant simulations and calculations in R a free statistical software environment. The second edition adds many new examples exercises and explanations to deepen understanding of the ideas clarify subtle concepts and respond to feedback from many students and readers. New supplementary online resources have been developed including animations and interactive visualizations and the book has been updated to dovetail with these resources. Supplementary material is available on Joseph Blitzstein’s website www. stat110. net. The supplements include:Solutions to selected exercisesAdditional practice problemsHandouts including review material and sample exams Animations and interactive visualizations created in connection with the edX online version of Stat 110. Links to lecture videos available on ITunes U and YouTube There is also a complete instructor's solutions manual available to instructors who require the book for a course. | Introduction to Probability Second Edition

GBP 66.99
1

Handbook of Financial Risk Management

Handbook of Financial Risk Management

Developed over 20 years of teaching academic courses the Handbook of Financial Risk Management can be divided into two main parts: risk management in the financial sector; and a discussion of the mathematical and statistical tools used in risk management. This comprehensive text offers readers the chance to develop a sound understanding of financial products and the mathematical models that drive them exploring in detail where the risks are and how to manage them. Key Features: Written by an author with both theoretical and applied experience Ideal resource for students pursuing a master’s degree in finance who want to learn risk management Comprehensive coverage of the key topics in financial risk management Contains 114 exercises with solutions provided online at www. crcpress. com/9781138501874

GBP 240.00
1

Advances in Distance Learning in Times of Pandemic

Advances in Distance Learning in Times of Pandemic

The book Advances in Distance Learning in Times of Pandemic is devoted to the issues and challenges faced by universities in the field of distance learning in COVID-19 times. It covers both the theoretical and practical aspects connected to distance education. It elaborates on issues regarding distance learning its challenges assessment by students and their expectations the use of tools to improve distance learning and the functioning of e-learning in the industry 4. 0 and society 5. 0 eras. The book also devotes a lot of space to the issues of Web 3. 0 in university e-learning quality assurance and knowledge management. The aim and scope of this book is to draw a holistic picture of ongoing online teaching-activities before and during the lockdown period and present the meaning and future of e-learning from students’ points of view taking into consideration their attitudes and expectations as well as industry 4. 0 and society 5. 0 aspects. The book presents the approach to distance learning and how it has changed especially during a pandemic that revolutionized education. It highlights • the function of online education and how that has changed before and during the pandemic. • how e-learning is beneficial in promoting digital citizenship. • distance learning characteristic in the era of industry 4. 0 and society 5. 0. • how the era of industry 4. 0 treats distance learning as a desirable form of education. The book covers both scientific and educational aspects and can be useful for university-level undergraduate postgraduate and research-grade courses and can be referred to by anyone interested in exploring the diverse aspects of distance learning.

GBP 110.00
1

Computational Statistics Handbook with MATLAB

Computational Statistics Handbook with MATLAB

A Strong Practical Focus on Applications and AlgorithmsComputational Statistics Handbook with MATLAB® Third Edition covers today’s most commonly used techniques in computational statistics while maintaining the same philosophy and writing style of the bestselling previous editions. The text keeps theoretical concepts to a minimum emphasizing the implementation of the methods. New to the Third EditionThis third edition is updated with the latest version of MATLAB and the corresponding version of the Statistics and Machine Learning Toolbox. It also incorporates new sections on the nearest neighbor classifier support vector machines model checking and regularization partial least squares regression and multivariate adaptive regression splines. Web ResourceThe authors include algorithmic descriptions of the procedures as well as examples that illustrate the use of algorithms in data analysis. The MATLAB code examples and data sets are available online.

GBP 44.99
1

Missing Data Analysis in Practice

Missing Data Analysis in Practice

Missing Data Analysis in Practice provides practical methods for analyzing missing data along with the heuristic reasoning for understanding the theoretical underpinnings. Drawing on his 25 years of experience researching teaching and consulting in quantitative areas the author presents both frequentist and Bayesian perspectives. He describes easy-to-implement approaches the underlying assumptions and practical means for assessing these assumptions. Actual and simulated data sets illustrate important concepts with the data sets and codes available online. The book underscores the development of missing data methods and their adaptation to practical problems. It mainly focuses on the traditional missing data problem. The author also shows how to use the missing data framework in many other statistical problems such as measurement error finite population inference disclosure limitation combing information from multiple data sources and causal inference.

GBP 44.99
1

Applied Linear Regression for Longitudinal Data With an Emphasis on Missing Observations

Applied Linear Regression for Longitudinal Data With an Emphasis on Missing Observations

This book introduces best practices in longitudinal data analysis at intermediate level with a minimum number of formulas without sacrificing depths. It meets the need to understand statistical concepts of longitudinal data analysis by visualizing important techniques instead of using abstract mathematical formulas. Different solutions such as multiple imputation are explained conceptually and consequences of missing observations are clarified using visualization techniques. Key features include the following: Provides datasets and examples online Gives state-of-the-art methods of dealing with missing observations in a non-technical way with a special focus on sensitivity analysis Conceptualises the analysis of comparative (experimental and observational) studies It is the ideal companion for researchers and students in epidemiological health and social and behavioral sciences working with longitudinal studies without a mathematical background. | Applied Linear Regression for Longitudinal Data With an Emphasis on Missing Observations

GBP 89.99
1

A Handbook of Statistical Analyses using SAS

A Handbook of Statistical Analyses using SAS

Updated to reflect SAS 9. 2 A Handbook of Statistical Analyses using SAS Third Edition continues to provide a straightforward description of how to conduct various statistical analyses using SAS. Each chapter shows how to use SAS for a particular type of analysis. The authors cover inference analysis of variance regression generalized linear models longitudinal data survival analysis principal components analysis factor analysis cluster analysis discriminant function analysis and correspondence analysis. They demonstrate the analyses through real-world examples including methadone maintenance treatment the relation of cirrhosis deaths to alcohol consumption a sociological study of children heart transplant treatment and crime rate determinants. With the data sets and SAS code available online this book remains the go-to resource for learning how to use SAS for many kinds of statistical analysis. It serves as a stepping stone to the wider resources available to SAS users.

GBP 180.00
1

Sets Functions and Logic An Introduction to Abstract Mathematics Third Edition

Sets Functions and Logic An Introduction to Abstract Mathematics Third Edition

Keith Devlin. You know him. You've read his columns in MAA Online you've heard him on the radio and you've seen his popular mathematics books. In between all those activities and his own research he's been hard at work revising Sets Functions and Logic his standard-setting text that has smoothed the road to pure mathematics for legions of undergraduate students. Now in its third edition Devlin has fully reworked the book to reflect a new generation. The narrative is more lively and less textbook-like. Remarks and asides link the topics presented to the real world of students' experience. The chapter on complex numbers and the discussion of formal symbolic logic are gone in favor of more exercises and a new introductory chapter on the nature of mathematics-one that motivates readers and sets the stage for the challenges that lie ahead. Students crossing the bridge from calculus to higher mathematics need and deserve all the help they can get. Sets Functions and Logic Third Edition is an affordable little book that all of your transition-course students not only can afford but will actually read and enjoy and learn from. About the AuthorDr. Keith Devlin is Executive Director of Stanford University's Center for the Study of Language and Information and a Consulting Professor of Mathematics at Stanford. He has written 23 books one interactive book on CD-ROM and over 70 published research articles. He is a Fellow of the American Association for the Advancement of Science a World Economic Forum Fellow and a former member of the Mathematical Sciences Education Board of the National Academy of Sciences . Dr. Devlin is also one of the world's leading popularizers of mathematics. Known as The Math Guy on NPR's Weekend Edition he is a frequent contributor to other local and national radio and TV shows in the US and Britain writes a monthly column for the Web journal MAA Online and regularly writes on mathematics and co | Sets Functions and Logic An Introduction to Abstract Mathematics Third Edition

GBP 175.00
1

Building a Platform for Data-Driven Pandemic Prediction From Data Modelling to Visualisation - The CovidLP Project

Building a Platform for Data-Driven Pandemic Prediction From Data Modelling to Visualisation - The CovidLP Project

This book is about building platforms for pandemic prediction. It provides an overview of probabilistic prediction for pandemic modeling based on a data-driven approach. It also provides guidance on building platforms with currently available technology using tools such as R Shiny and interactive plotting programs. The focus is on the integration of statistics and computing tools rather than on an in-depth analysis of all possibilities on each side. Readers can follow different reading paths through the book depending on their needs. The book is meant as a basis for further investigation of statistical modelling implementation tools monitoring aspects and software functionalities. Features: A general but parsimonious class of models to perform statistical prediction for epidemics using a Bayesian approach Implementation of automated routines to obtain daily prediction results How to interactively visualize the model results Strategies for monitoring the performance of the predictions and identifying potential issues in the results Discusses the many decisions required to develop and publish online platforms Supplemented by an R package and its specific functionalities to model epidemic outbreaks The book is geared towards practitioners with an interest in the development and presentation of results in an online platform of statistical analysis of epidemiological data. The primary audience includes applied statisticians biostatisticians computer scientists epidemiologists and professionals interested in learning more about epidemic modelling in general including the COVID-19 pandemic and platform building. The authors are professors at the Statistics Department at Universidade Federal de Minas Gerais. Their research records exhibit contributions applied to a number of areas of Science including Epidemiology. Their research activities include books published with Chapman and Hall/CRC and papers in high quality journals. They have also been involved with academic management of graduate programs in Statistics and one of them is currently the President of the Brazilian Statistical Association. | Building a Platform for Data-Driven Pandemic Prediction From Data Modelling to Visualisation - The CovidLP Project

GBP 56.99
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Data Science A First Introduction

Data Science A First Introduction

Data Science: A First Introduction focuses on using the R programming language in Jupyter notebooks to perform data manipulation and cleaning create effective visualizations and extract insights from data using classification regression clustering and inference. The text emphasizes workflows that are clear reproducible and shareable and includes coverage of the basics of version control. All source code is available online demonstrating the use of good reproducible project workflows. Based on educational research and active learning principles the book uses a modern approach to R and includes accompanying autograded Jupyter worksheets for interactive self-directed learning. The book will leave readers well-prepared for data science projects. The book is designed for learners from all disciplines with minimal prior knowledge of mathematics and programming. The authors have honed the material through years of experience teaching thousands of undergraduates in the University of British Columbia’s DSCI100: Introduction to Data Science course. | Data Science A First Introduction

GBP 48.99
1

CRC Standard Mathematical Tables and Formulas

CRC Standard Mathematical Tables and Formulas

Containing more than 6 000 entries CRC Standard Mathematical Tables and Formulas 33rd Edition continues to provide essential formulas tables figures and detailed descriptions. The newest edition of this popular series also features many diagrams group tables and integrals that are not available online. This edition also incorporates important topics such as max plus algebra financial options pseudospectra and proof methods. Newly updated topics reflecting new results include couple analogues radar and significant equations of mathematics. New features of the 33rd edition include: Larger trim size five new topics and topics which have been modified to update results Provides practical ready-to-use information and covers important topics that are unfamiliar to many readers such as visual proofs and sequences Includes hard-to-find and more complete information than found in the Internet such as table of conformal mappings and integral tables Adds descriptions of new functions: Lambert prolate spheroidal and Weierstrass Even though the book has been updated it retains the same successful format of previous editions in that material is still presented in a multi-sectional format.

GBP 94.99
1

Solution Techniques for Elementary Partial Differential Equations

Solution Techniques for Elementary Partial Differential Equations

In my opinion this is quite simply the best book of its kind that I have seen thus far. —Professor Peter Schiavone University of Alberta from the Foreword to the Fourth Edition Praise for the previous editions An ideal tool for students taking a first course in PDEs as well as for the lecturers who teach such courses. —Marian Aron Plymouth University UK This is one of the best books on elementary PDEs this reviewer has read so far. Highly recommended. —CHOICE Solution Techniques for Elementary Partial Differential Equations Fourth Edition remains a top choice for a standard undergraduate-level course on partial differential equations (PDEs). It provides a streamlined direct approach to developing students’ competence in solving PDEs and offers concise easily understood explanations and worked examples that enable students to see the techniques in action. New to the Fourth Edition Two additional sections A larger number and variety of worked examples and exercises A companion pdf file containing more detailed worked examples to supplement those in the book which can be used in the classroom and as an aid to online teaching

GBP 56.99
1

Applied Bayesian Forecasting and Time Series Analysis

Applied Bayesian Forecasting and Time Series Analysis

Practical in its approach Applied Bayesian Forecasting and Time Series Analysis provides the theories methods and tools necessary for forecasting and the analysis of time series. The authors unify the concepts model forms and modeling requirements within the framework of the dynamic linear mode (DLM). They include a complete theoretical development of the DLM and illustrate each step with analysis of time series data. Using real data sets the authors: Explore diverse aspects of time series including how to identify structure explain observed behavior model structures and behaviors and interpret analyses to make informed forecasts Illustrate concepts such as component decomposition fundamental model forms including trends and cycles and practical modeling requirements for routine change and unusual events Conduct all analyses in the BATS computer programs furnishing online that program and the more than 50 data sets used in the text The result is a clear presentation of the Bayesian paradigm: quantified subjective judgements derived from selected models applied to time series observations. Accessible to undergraduates this unique volume also offers complete guidelines valuable to researchers practitioners and advanced students in statistics operations research and engineering.

GBP 56.99
1

DNA Methylation Microarrays Experimental Design and Statistical Analysis

DNA Methylation Microarrays Experimental Design and Statistical Analysis

Providing an interface between dry-bench bioinformaticians and wet-lab biologists DNA Methylation Microarrays: Experimental Design and Statistical Analysis presents the statistical methods and tools to analyze high-throughput epigenomic data in particular DNA methylation microarray data. Since these microarrays share the same underlying principles as gene expression microarrays many of the analyses in the text also apply to microarray-based gene expression and histone modification (ChIP-on-chip) studies. After introducing basic statistics the book describes wet-bench technologies that produce the data for analysis and explains how to preprocess the data to remove systematic artifacts resulting from measurement imperfections. It then explores differential methylation and genomic tiling arrays. Focusing on exploratory data analysis the next several chapters show how cluster and network analyses can link the functions and roles of unannotated DNA elements with known ones. The book concludes by surveying the open source software (R and Bioconductor) public databases and other online resources available for microarray research. Requiring only limited knowledge of statistics and programming this book helps readers gain a solid understanding of the methodological foundations of DNA microarray analysis. | DNA Methylation Microarrays Experimental Design and Statistical Analysis

GBP 59.99
1

Exploring Linear Algebra Labs and Projects with MATLAB

Exploring Linear Algebra Labs and Projects with MATLAB

Exploring Linear Algebra: Labs and Projects with MATLAB® is a hands-on lab manual that can be used by students and instructors in classrooms every day to guide the exploration of the theory and applications of linear algebra. For the most part labs discussed in the book can be used individually or in a sequence. Each lab consists of an explanation of material with integrated exercises. Some labs are split into multiple subsections and thus exercises are separated by those subsections. The exercise sections integrate problems using Mathematica demonstrations (an online tool that can be used with a browser with Java capabilities) and MATLAB® coding. This allows students to discover the theory and applications of linear algebra in a meaningful and memorable way. Features: The book’s inquiry-based approach promotes student interaction Each chapter contains a project set which consists of application-driven projects emphasizing the chapter’s materials Adds a project component to any Linear Algebra course Explores many applications to a variety of fields that can promote research projects Employs MATLAB® to calculate and explore concepts and theories of linear algebra | Exploring Linear Algebra Labs and Projects with MATLAB®

GBP 44.99
1

Surrogates Gaussian Process Modeling Design and Optimization for the Applied Sciences

Surrogates Gaussian Process Modeling Design and Optimization for the Applied Sciences

Surrogates: a graduate textbook or professional handbook on topics at the interface between machine learning spatial statistics computer simulation meta-modeling (i. e. emulation) design of experiments and optimization. Experimentation through simulation human out-of-the-loop statistical support (focusing on the science) management of dynamic processes online and real-time analysis automation and practical application are at the forefront. Topics include:Gaussian process (GP) regression for flexible nonparametric and nonlinear modeling. Applications to uncertainty quantification sensitivity analysis calibration of computer models to field data sequential design/active learning and (blackbox/Bayesian) optimization under uncertainty. Advanced topics include treed partitioning local GP approximation modeling of simulation experiments (e. g. agent-based models) with coupled nonlinear mean and variance (heteroskedastic) models. Treatment appreciates historical response surface methodology (RSM) and canonical examples but emphasizes contemporary methods and implementation in R at modern scale. Rmarkdown facilitates a fully reproducible tour complete with motivation from application to and illustration with compelling real-data examples. Presentation targets numerically competent practitioners in engineering physical and biological sciences. Writing is statistical in form but the subjects are not about statistics. Rather they’re about prediction and synthesis under uncertainty; about visualization and information design and decision making computing and clean code. | Surrogates Gaussian Process Modeling Design and Optimization for the Applied Sciences

GBP 38.99
1

Line Integral Methods for Conservative Problems

Line Integral Methods for Conservative Problems

Line Integral Methods for Conservative Problems explains the numerical solution of differential equations within the framework of geometric integration a branch of numerical analysis that devises numerical methods able to reproduce (in the discrete solution) relevant geometric properties of the continuous vector field. The book focuses on a large set of differential systems named conservative problems particularly Hamiltonian systems. Assuming only basic knowledge of numerical quadrature and Runge–Kutta methods this self-contained book begins with an introduction to the line integral methods. It describes numerous Hamiltonian problems encountered in a variety of applications and presents theoretical results concerning the main instance of line integral methods: the energy-conserving Runge–Kutta methods also known as Hamiltonian boundary value methods (HBVMs). The authors go on to address the implementation of HBVMs in order to recover in the numerical solution what was expected from the theory. The book also covers the application of HBVMs to handle the numerical solution of Hamiltonian partial differential equations (PDEs) and explores extensions of the energy-conserving methods. With many examples of applications this book provides an accessible guide to the subject yet gives you enough details to allow concrete use of the methods. MATLAB codes for implementing the methods are available online.

GBP 59.99
1

Algebra & Geometry An Introduction to University Mathematics

Algebra & Geometry An Introduction to University Mathematics

Algebra & Geometry: An Introduction to University Mathematics Second Edition provides a bridge between high school and undergraduate mathematics courses on algebra and geometry. The author shows students how mathematics is more than a collection of methods by presenting important ideas and their historical origins throughout the text. He incorporates a hands-on approach to proofs and connects algebra and geometry to various applications. The text focuses on linear equations polynomial equations and quadratic forms. The first few chapters cover foundational topics including the importance of proofs and a discussion of the properties commonly encountered when studying algebra. The remaining chapters form the mathematical core of the book. These chapters explain the solutions of different kinds of algebraic equations the nature of the solutions and the interplay between geometry and algebra. New to the second edition Several updated chapters plus an all-new chapter discussing the construction of the real numbers by means of approximations by rational numbers Includes fifteen short ‘essays’ that are accessible to undergraduate readers but which direct interested students to more advanced developments of the material Expanded references Contains chapter exercises with solutions provided online at www. routledge. com/9780367563035 | Algebra & Geometry An Introduction to University Mathematics

GBP 52.99
1

Randomization Bootstrap and Monte Carlo Methods in Biology

Randomization Bootstrap and Monte Carlo Methods in Biology

Modern computer-intensive statistical methods play a key role in solving many problems across a wide range of scientific disciplines. Like its bestselling predecessors the fourth edition of Randomization Bootstrap and Monte Carlo Methods in Biology illustrates a large number of statistical methods with an emphasis on biological applications. The focus is now on the use of randomization bootstrapping and Monte Carlo methods in constructing confidence intervals and doing tests of significance. The text provides comprehensive coverage of computer-intensive applications with data sets available online. Features Presents an overview of computer-intensive statistical methods and applications in biology Covers a wide range of methods including bootstrap Monte Carlo ANOVA regression and Bayesian methods Makes it easy for biologists researchers and students to understand the methods used Provides information about computer programs and packages to implement calculations particularly using R code Includes a large number of real examples from a range of biological disciplines Written in an accessible style with minimal coverage of theoretical details this book provides an excellent introduction to computer-intensive statistical methods for biological researchers. It can be used as a course text for graduate students as well as a reference for researchers from a range of disciplines. The detailed worked examples of real applications will enable practitioners to apply the methods to their own biological data.

GBP 44.99
1

Machine Learning for Factor Investing: R Version

Machine Learning for Factor Investing: R Version

Machine learning (ML) is progressively reshaping the fields of quantitative finance and algorithmic trading. ML tools are increasingly adopted by hedge funds and asset managers notably for alpha signal generation and stocks selection. The technicality of the subject can make it hard for non-specialists to join the bandwagon as the jargon and coding requirements may seem out of reach. Machine Learning for Factor Investing: R Version bridges this gap. It provides a comprehensive tour of modern ML-based investment strategies that rely on firm characteristics. The book covers a wide array of subjects which range from economic rationales to rigorous portfolio back-testing and encompass both data processing and model interpretability. Common supervised learning algorithms such as tree models and neural networks are explained in the context of style investing and the reader can also dig into more complex techniques like autoencoder asset returns Bayesian additive trees and causal models. All topics are illustrated with self-contained R code samples and snippets that are applied to a large public dataset that contains over 90 predictors. The material along with the content of the book is available online so that readers can reproduce and enhance the examples at their convenience. If you have even a basic knowledge of quantitative finance this combination of theoretical concepts and practical illustrations will help you learn quickly and deepen your financial and technical expertise.

GBP 66.99
1

Machine Learning for Factor Investing Python Version

Machine Learning for Factor Investing Python Version

Machine learning (ML) is progressively reshaping the fields of quantitative finance and algorithmic trading. ML tools are increasingly adopted by hedge funds and asset managers notably for alpha signal generation and stocks selection. The technicality of the subject can make it hard for non-specialists to join the bandwagon as the jargon and coding requirements may seem out-of-reach. Machine learning for factor investing: Python version bridges this gap. It provides a comprehensive tour of modern ML-based investment strategies that rely on firm characteristics. The book covers a wide array of subjects which range from economic rationales to rigorous portfolio back-testing and encompass both data processing and model interpretability. Common supervised learning algorithms such as tree models and neural networks are explained in the context of style investing and the reader can also dig into more complex techniques like autoencoder asset returns Bayesian additive trees and causal models. All topics are illustrated with self-contained Python code samples and snippets that are applied to a large public dataset that contains over 90 predictors. The material is available online so that readers can reproduce and enhance the examples at their convenience. If you have even a basic knowledge of quantitative finance this combination of theoretical concepts and practical illustrations will help you learn quickly and deepen your financial and technical expertise. | Machine Learning for Factor Investing Python Version

GBP 66.99
1

Search Engine Optimization and Marketing A Recipe for Success in Digital Marketing

Search Engine Optimization and Marketing A Recipe for Success in Digital Marketing

Search Engine Optimization and Marketing: A Recipe for Success in Digital Marketing analyzes the web traffic for online promotion that includes search engine optimization and search engine marketing. After careful analysis of the nuances of the semantic web of search engine optimization (SEO) and its practical set up readers can put their best foot forward for SEO setup link-building for SERP establishment various methods with requisite algorithms and programming codes with process inferences. The book offers comprehensive coverage of essential topics including: • The concept of SEM and SEO • The mechanism of crawler program concepts of keywords • Keyword generation tools • Page ranking mechanism and indexing • Concepts of title meta alt tags • Concepts of PPC/PPM/CTR • SEO/SEM strategies • Anchor text and setting up • Query-based search While other books are focused on the traditional explanation of digital marketing theoretical features of SEO and SEM for keyword set up with link-building this book focuses on the practical applications of the above-mentioned concepts for effective SERP generation. Another unique aspect of this book is its abundance of handy workarounds to set up the techniques for SEO a topic too often neglected by other works in the field. This book is an invaluable resource for social media analytics researchers and digital marketing students. | Search Engine Optimization and Marketing A Recipe for Success in Digital Marketing

GBP 105.00
1

Advances in Complex Decision Making Using Machine Learning and Tools for Service-Oriented Computing

Advances in Complex Decision Making Using Machine Learning and Tools for Service-Oriented Computing

The rapidly evolving business and technology landscape demands sophisticated decision-making tools to stay ahead of the curve. Advances in Complex Decision Making: Using Machine Learning and Tools for Service-Oriented Computing is a cutting-edge technical guide exploring the latest decision-making technology advancements. This book provides a comprehensive overview of machine learning algorithms and examines their applications in complex decision-making systems in a service-oriented framework. The authors also delve into service-oriented computing and how it can be used to build complex systems that support decision making. Many real-world examples are discussed in this book to provide a practical insight into how discussed techniques can be applied in various domains including distributed computing cloud computing IoT and other online platforms. For researchers students data scientists and technical practitioners this book offers a deep dive into the current developments of machine learning algorithms and their applications in service-oriented computing. This book discusses various topics including Fuzzy Decisions ELICIT OWA aggregation Directed Acyclic Graph RNN LSTM GRU Type-2 Fuzzy Decision Evidential Reasoning algorithm and robust optimisation algorithms. This book is essential for anyone interested in the intersection of machine learning and service computing in complex decision-making systems. | Advances in Complex Decision Making Using Machine Learning and Tools for Service-Oriented Computing

GBP 44.99
1

Python Packages

Python Packages

Python Packages introduces Python packaging at an introductory and practical level that’s suitable for those with no previous packaging experience. Despite this the text builds up to advanced topics such as automated testing creating documentation versioning and updating a package and implementing continuous integration and deployment. Covering the entire Python packaging life cycle this essential guide takes readers from package creation all the way to effective maintenance and updating. Python Packages focuses on the use of current and best-practice packaging tools and services like poetry cookiecutter pytest sphinx GitHub and GitHub Actions. Features: The book’s source code is available online as a GitHub repository where it is collaborated on automatically tested and built in real time as changes are made; demonstrating the use of good reproducible and clear project workflows. Covers not just the process of creating a package but also how to document it test it publish it to the Python Package Index (PyPI) and how to properly version and update it. All concepts in the book are demonstrated using examples. Readers can follow along creating their own Python packages using the reproducible code provided in the text. Focuses on a modern approach to Python packaging with emphasis on automating and streamlining the packaging process using new and emerging tools such as poetry and GitHub Actions.

GBP 35.99
1