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Guide to Cybersecurity in Digital Transformation: Trends, Methods, Technologies, Applications and Best Practices (Advances in Information Security #103)
by Dietmar P.F. MöllerIn today’s digital transformation environments, a rigorous cybersecurity approach to effective risk management — including contingency planning, outlining immediate actions, preparing post-breach responses — is central to defending organizations’ interconnected computer systems, networks, and infrastructure resources from malicious cyber-attacks.Specifically, cybersecurity technologies, processes, and practices need to be generalized and applied to intrusion detection and prevention measures. This entails analyzing profiles of cyber-attackers and building cyber-attack models for behavior simulation that can effectively counter such attacks. This comprehensive volume aims to cover all essential aspects of cybersecurity in digital transformation and to provide a framework for considering the many objectives and requirements involved. In addition to introducing theoretical foundations, the work also offers practical techniques for defending against malicious cybercriminals.Topics and features:Explores cybersecurity’s impact on the dynamics of interconnected, complex cyber- and physical systems, infrastructure resources, and networksProvides numerous examples of applications and best practicesConsiders methods that organizations can use to assess their cybersecurity awareness and/or strategyDescribes anomaly intrusion detection, a key tool in thwarting both malware and theft (whether by insiders or external parties) of corporate dataAddresses cyber-attacker profiles, cyber-attack models and simulation, cybersecurity ontology, access-control mechanisms, and policies for handling ransomware attacksDiscusses the NIST Cybersecurity Framework, MITRE Adversarial Tactics, Techniques and Common Knowledge, CIS Critical Security Controls, and the ISA/IEC 62442 Cybersecurity StandardGathering all the relevant information, this practical guide is eminently suitable as a self-study resource for engineers, scientists, computer scientists, and chief information officers. Further, with its many examples of best practices, it can serve as an excellent text for graduate-level courses and research into cybersecurity.Dietmar P. F. Möller, a retired full professor, is affiliated with the Institute for Mathematics at Clausthal University of Technology, Germany. He was an author of several other Springer titles, including Guide to Automotive Connectivity and Cybersecurity.
Guide to Data Privacy: Models, Technologies, Solutions (Undergraduate Topics in Computer Science)
by Vicenç TorraData privacy technologies are essential for implementing information systems with privacy by design.Privacy technologies clearly are needed for ensuring that data does not lead to disclosure, but also that statistics or even data-driven machine learning models do not lead to disclosure. For example, can a deep-learning model be attacked to discover that sensitive data has been used for its training? This accessible textbook presents privacy models, computational definitions of privacy, and methods to implement them. Additionally, the book explains and gives plentiful examples of how to implement—among other models—differential privacy, k-anonymity, and secure multiparty computation.Topics and features:Provides integrated presentation of data privacy (including tools from statistical disclosure control, privacy-preserving data mining, and privacy for communications)Discusses privacy requirements and tools for different types of scenarios, including privacy for data, for computations, and for usersOffers characterization of privacy models, comparing their differences, advantages, and disadvantagesDescribes some of the most relevant algorithms to implement privacy modelsIncludes examples of data protection mechanismsThis unique textbook/guide contains numerous examples and succinctly and comprehensively gathers the relevant information. As such, it will be eminently suitable for undergraduate and graduate students interested in data privacy, as well as professionals wanting a concise overview.Vicenç Torra is Professor with the Department of Computing Science at Umeå University, Umeå, Sweden.
Guide to Deep Learning Basics: Logical, Historical and Philosophical Perspectives
by Sandro SkansiThis stimulating text/reference presents a philosophical exploration of the conceptual foundations of deep learning, presenting enlightening perspectives that encompass such diverse disciplines as computer science, mathematics, logic, psychology, and cognitive science. The text also highlights select topics from the fascinating history of this exciting field, including the pioneering work of Rudolf Carnap, Warren McCulloch, Walter Pitts, Bulcsú László, and Geoffrey Hinton.Topics and features:Provides a brief history of mathematical logic, and discusses the critical role of philosophy, psychology, and neuroscience in the history of AIPresents a philosophical case for the use of fuzzy logic approaches in AIInvestigates the similarities and differences between the Word2vec word embedding algorithm, and the ideas of Wittgenstein and Firth on linguisticsExamines how developments in machine learning provide insights into the philosophical challenge of justifying inductive inferencesDebates, with reference to philosophical anthropology, whether an advanced general artificial intelligence might be considered as a living beingInvestigates the issue of computational complexity through deep-learning strategies for understanding AI-complete problems and developing strong AIExplores philosophical questions at the intersection of AI and transhumanismThis inspirational volume will rekindle a passion for deep learning in those already experienced in coding and studying this discipline, and provide a philosophical big-picture perspective for those new to the field.
Guide to Differential Privacy Modifications: A Taxonomy of Variants and Extensions (SpringerBriefs in Computer Science)
by Balázs Pejó Damien DesfontainesShortly after it was first introduced in 2006, differential privacy became the flagship data privacy definition. Since then, numerous variants and extensions were proposed to adapt it to different scenarios and attacker models. In this work, we propose a systematic taxonomy of these variants and extensions. We list all data privacy definitions based on differential privacy, and partition them into seven categories, depending on which aspect of the original definition is modified.These categories act like dimensions: Variants from the same category cannot be combined, but variants from different categories can be combined to form new definitions. We also establish a partial ordering of relative strength between these notions by summarizing existing results. Furthermore, we list which of these definitions satisfy some desirable properties, like composition, post-processing, and convexity by either providing a novel proof or collecting existing ones.
Guide to Digital Forensics
by Joakim KävrestadThis work introduces the reader to the world of digital forensics in a practical and accessible manner. The text was written to fulfill a need for a book that introduces forensic methodology and sound forensic thinking, combined with hands-on examples for common tasks in a computer forensic examination. The author has several years of experience as a computer forensics examiner and is now working as a university-level lecturer. Guide to Digital Forensics: A Concise and Practical Introduction is intended for students that are looking for an introduction to computer forensics and can also be used as a collection of instructions for practitioners. The aim is to describe and explain the steps taken during a forensic examination, with the intent of making the reader aware of the constraints and considerations that apply during a forensic examination in law enforcement and in the private sector. Upon reading this book, the reader should have a proper overview of the field of digital forensics, starting them on the journey of becoming a computer forensics expert.
Guide to Digital Innovation in the Cultural and Creative Industry (SAGE Works)
by Yong Xiang Sunghan Ryu Weimin ZhangThe digital age has brought significant changes to the cultural and creative industries, making it challenging to keep up with the latest trends. The Guide to Digital Innovation in the Cultural and Creative Industry is an informative resource that can help you navigate the revolution. It not only provides a comprehensive understanding of how digital transformation affects existing industries but also outlines emerging business opportunities. Whether you′re an experienced professional or a beginner, this book is an essential resource that will equip you with the knowledge and tools you need to succeed in the rapidly evolving landscape of the cultural and creative industries. Dive into: Democratizing creation: Discover how digital tools break down barriers and empower creators of all levels. From platforms to possibilities: Explore online video streaming, ebook publishing, virtual museums, and more, witnessing the rise of innovative business models. Cutting-edge tech, boundless potential: Delve into AI, blockchain, VR/AR, and other emerging technologies, understanding how they reshape content production, distribution, and consumption. Case studies that examine real-world scenarios, from the digital subscriptions of the New York Times to music consumption in the Spotify era.
Guide to Digital Innovation in the Cultural and Creative Industry (SAGE Works)
by Yong Xiang Sunghan Ryu Weimin ZhangThe digital age has brought significant changes to the cultural and creative industries, making it challenging to keep up with the latest trends. The Guide to Digital Innovation in the Cultural and Creative Industry is an informative resource that can help you navigate the revolution. It not only provides a comprehensive understanding of how digital transformation affects existing industries but also outlines emerging business opportunities. Whether you′re an experienced professional or a beginner, this book is an essential resource that will equip you with the knowledge and tools you need to succeed in the rapidly evolving landscape of the cultural and creative industries. Dive into: Democratizing creation: Discover how digital tools break down barriers and empower creators of all levels. From platforms to possibilities: Explore online video streaming, ebook publishing, virtual museums, and more, witnessing the rise of innovative business models. Cutting-edge tech, boundless potential: Delve into AI, blockchain, VR/AR, and other emerging technologies, understanding how they reshape content production, distribution, and consumption. Case studies that examine real-world scenarios, from the digital subscriptions of the New York Times to music consumption in the Spotify era.
Guide to Disaster-Resilient Communication Networks (Computer Communications and Networks)
by Jacek Rak David HutchisonThis authoritative volume presents a comprehensive guide to the evaluation and design of networked systems with improved disaster resilience. The text offers enlightening perspectives on issues relating to all major failure scenarios, including natural disasters, disruptions caused by adverse weather conditions, massive technology-related failures, and malicious human activities.Topics and features: describes methods and models for the analysis and evaluation of disaster-resilient communication networks; examines techniques for the design and enhancement of disaster-resilient systems; provides a range of schemes and algorithms for resilient systems; reviews various advanced topics relating to resilient communication systems; presents insights from an international selection of more than 100 expert researchers working across the academic, industrial, and governmental sectors.This practically-focused monograph, providing invaluable support on topics of resilient networking equipment and software, is an essential reference for network professionals including network and networked systems operators, networking equipment vendors, providers of essential services, and regulators. The work can also serve as a supplementary textbook for graduate and PhD courses on networked systems resilience.
Guide to Discrete Mathematics: An Accessible Introduction to the History, Theory, Logic and Applications (Texts in Computer Science)
by Gerard O'ReganThis stimulating textbook presents a broad and accessible guide to the fundamentals of discrete mathematics, highlighting how the techniques may be applied to various exciting areas in computing. The text is designed to motivate and inspire the reader, encouraging further study in this important skill. Features: This book provides an introduction to the building blocks of discrete mathematics, including sets, relations and functions; describes the basics of number theory, the techniques of induction and recursion, and the applications of mathematical sequences, series, permutations, and combinations; presents the essentials of algebra; explains the fundamentals of automata theory, matrices, graph theory, cryptography, coding theory, language theory, and the concepts of computability and decidability; reviews the history of logic, discussing propositional and predicate logic, as well as advanced topics such as the nature of theorem proving; examines the field of software engineering, including software reliability and dependability and describes formal methods; investigates probability and statistics and presents an overview of operations research and financial mathematics.
Guide to Distributed Algorithms: Design, Analysis and Implementation Using Python (Undergraduate Topics in Computer Science)
by K. ErciyesThe study of distributed algorithms provides the needed background in many real-life applications, such as: distributed real-time systems, wireless sensor networks, mobile ad hoc networks and distributed databases. The main goal of Guide to Distributed Algorithms is to provide a detailed study of the design and analysis methods of distributed algorithms and to supply the implementations of most of the presented algorithms in Python language, which is the unique feature of the book not found in any other contemporary books on distributed computing. Topics and features: Presents comprehensive design methods for distributed algorithms Provides detailed analysis for the algorithms presented Uses graph templates to demonstrate the working of algorithms Provides working Python code for most of the algorithms presented This unique textbook/study manual can serve as a comprehensive manual of distributed algorithms for Computer Science and non-CS majors as well as practitioners of distributed algorithms in research projects.
Guide to Distributed Simulation with HLA
by Okan Topçu Halit OğuztüzünThis invaluable textbook/reference provides a hands-on guide to the application of good software development practices to the construction of distributed simulation systems, with a particular focus on High Level Architecture (HLA). Emphasizing a learning-by-doing approach supported by examples, the text offers practical advice on real-world development issues for all engineers and programmers entering the field.Topics and features: explains how to rapidly develop an HLA federation, offering an implemented sample for each service area of the HLA federate interface specification; describes this implementation using the freely available software tools SimGe and RACoN; provides numerous step-by-step examples, code snippets, and case studies, as well as links to downloadable sample source code; uses the Microsoft .NET platform and the C# programming language in all examples and case studies; includes review questions throughout the book for further study; examines not only federate application development, but also object model construction; discusses the employment of HLA in multi-agent simulations.Providing an accessible introduction and all-in-one resource for HLA-based distributed simulation development, this book is an essential guide for students and practitioners training in distributed simulation and distributed interactive simulation.
Guide to Dynamic Simulations of Rigid Bodies and Particle Systems
by Murilo G. CoutinhoThis book introduces the techniques needed to produce realistic simulations and animations of particle and rigid-body systems. The text focuses on both the theoretical and practical aspects of developing and implementing physically based dynamic-simulation engines. Each chapter examines numerous algorithms, describing their design and analysis in an accessible manner, without sacrificing depth of coverage or mathematical rigor. Features: examines the problem of computing an hierarchical representation of the geometric description of each simulated object, as well as the simulated world; discusses the use of discrete and continuous collision detection to handle thin or fast-moving objects; describes the computational techniques needed for determining all impulsive and contact forces between bodies with multiple simultaneous collisions and contacts; presents techniques that can be used to dynamically simulate articulated rigid bodies; concludes each chapter with exercises.
Guide to Efficient Software Design: An MVC Approach to Concepts, Structures, and Models (Texts in Computer Science)
by David P. VoorheesThis classroom-tested textbook presents an active-learning approach to the foundational concepts of software design. These concepts are then applied to a case study, and reinforced through practice exercises, with the option to follow either a structured design or object-oriented design paradigm. The text applies an incremental and iterative software development approach, emphasizing the use of design characteristics and modeling techniques as a way to represent higher levels of design abstraction, and promoting the model-view-controller (MVC) architecture.Topics and features: provides a case study to illustrate the various concepts discussed throughout the book, offering an in-depth look at the pros and cons of different software designs; includes discussion questions and hands-on exercises that extend the case study and apply the concepts to other problem domains; presents a review of program design fundamentals to reinforce understanding of the basic concepts; focuses on a bottom-up approach to describing software design concepts; introduces the characteristics of a good software design, emphasizing the model-view-controller as an underlying architectural principle; describes software design from both object-oriented and structured perspectives; examines additional topics on human-computer interaction design, quality assurance, secure design, design patterns, and persistent data storage design; discusses design concepts that may be applied to many types of software development projects; suggests a template for a software design document, and offers ideas for further learning.Students of computer science and software engineering will find this textbook to be indispensable for advanced undergraduate courses on programming and software design. Prior background knowledge and experience of programming is required, but familiarity in software design is not assumed.
Guide to Electricity and Magnetism: Using Mathematica for Calculations and Visualizations
by James W. RohlfThis is a “how to guide” for a calculus-based introductory course in electricity and magnetism. Students taking the subject at an intermediate or advanced level may also find it to be a useful reference. The calculations are performed in Mathematica, and stress graphical visualization, units, and numerical answers. The techniques show the student how to learn the physics without being hung up on the math. There is a continuing movement to introduce more advanced computational methods into lower-level physics courses. Mathematica is a unique tool in that code is written as "human readable" much like one writes a traditional equation on the board.Key Features: Concise summary of the physics concepts. Over 300 worked examples in Mathematica. Tutorial to allow a beginner to produce fast results. The companion code for this book can be found here: https://physics.bu.edu/~rohlf/code.html
Guide to FPGA Implementation of Arithmetic Functions
by Enrique Cantó Gustavo D. Sutter Jean-Pierre DeschampsThis book is designed both for FPGA users interested in developing new, specific components - generally for reducing execution times -and IP core designers interested in extending their catalog of specific components. The main focus is circuit synthesis and the discussion shows, for example, how a given algorithm executing some complex function can be translated to a synthesizable circuit description, as well as which are the best choices the designer can make to reduce the circuit cost, latency, or power consumption. This is not a book on algorithms. It is a book that shows how to translate efficiently an algorithm to a circuit, using techniques such as parallelism, pipeline, loop unrolling, and others. Numerous examples of FPGA implementation are described throughout this book and the circuits are modeled in VHDL. Complete and synthesizable source files are available for download.
Guide to Flow-Aware Networking
by Jerzy Domżał Robert Wójcik Andrzej JajszczykThis book provides a practical guide to flow-aware networking (FAN), one of the most promising new quality-of-service architectures for the Future Internet. The latest concepts are examined in detail, including coverage of approximate flow-aware networking. The scope and evolution of the debate on network neutrality is also discussed. Topics and features: provides a broad survey of flow-oriented approaches and solutions based on the concept of flows; presents a range of mechanisms for improving transmission performance of streaming flows under congestion; illustrates how problems caused by congestion may be solved in a multilayer environment, proposing new methods for enhancing transmission in wired-wireless FAN; analyzes aspects of fair transmission in FAN, reviewing algorithms that improve transmission of streaming flows during network failures; describes the implementation aspects of the cross-protect router; concludes each chapter with review questions, with answers provided at the end of the book.
Guide to Flow-Aware Networking: Challenges and Opportunities (Computer Communications and Networks #0)
by Jerzy Domżał Robert Wójcik Andrzej JajszczykThe book presents a comprehensive view on Flow-Aware Networking. It starts with a brief overview of the known QoS architectures based on the concept of a flow. Then, the original FAN concept is presented, along with its variations proposed by the authors. The next chapter covers a very valuable feature of the FAN architecture, namely its ability to assure net neutrality. The chapters that follow will discuss, in detail, a variety of issues making the FAN concept implementable, including congestion control, fairness, resilience to failures, service differentiation and degradation. The final chapter presents the test implementation of the FAN router, including the environment used and performance tests. Chapters are supplemented with problems to solve, along with their solutions. The pedagogical character of the book is supported by a number of illustrative examples contained in most of the chapters. At the end of the book, a glossary of the key terms is included, along with a comprehensive bibliography.Flow-based traffic management is currently becoming a mainstream. There is plenty of Quality of Service (QoS) techniques based on flows. Software-Defined Networking with its dominant protocol OpenFlow also follows this trend. Flow-Aware Networking (FAN) is a promising QoS architecture. Information on FAN can be found in various research papers. It is, therefore highly scattered. This book gathers practically all relevant information regarding FAN and puts it together.Quality of Service assurance is one of the key challenges of today’s Internet. The existing approaches to provide QoS do not meet expectations of network operators, managers and users although numerous efforts in this area have been reported. One of the most promising concepts is the Flow-Aware Network (FAN). FAN can play a key role in assuring the net neutrality, smoothly combining interests of all the involved parties. The authors of the proposal have been involved in FAN research practically since its inception at the start of the 21st century. The book reports the wide experiences the authors accumulated in the subject area during the work on common FAN-related projects conducted with the team of James Roberts that proposed the original FAN concept as well as other leading research groups in Europe and the USA. One of the aims of the book is to accompany courses taught by the authors.
Guide to Framing Design Practice for UX (Synthesis Lectures on Human-Centered Informatics)
by John LongThe scope of the book is UX. It presents a comprehensive guide for readers to better engage with the framing of UX design practice. The guide characterises UX as a movement, whose members are developing shared ideas to specify and to implement HCI (Human-Computer Interaction) as UX. The book is based on the analysis of the conduct and reporting of framing UX design practice, contributed by experienced UX practitioners. It surveys the various means by which UX practitioners conduct and report their design practices. These include trial and error; implement, test, and specify; and implement, evaluate, and iterate. These practices apply UX frameworks, UX approaches, and UX methods and are typically reported in the form of UX case studies. The book differs from top-down, formal, and framework-driven approaches. In contrast, it takes a bottom-up, informal, and practice-driven approach. In a dynamic field such as UX, there is seldom time to stop and think about the wider issues associated with design practice and its related trends. But this book creates that opportunity for UX practitioners to locate and reflect on their design practice—what they are doing and why they are doing it. The guide creates a space in which UX practitioners are informed of current trends that they can incorporate into their own workflows. Readers benefiting from this book include those working in customer experience design, experience-centred design, and human experience design. It will also be of interest to undergraduate and graduate students trying to make sense of the different ways of conducting and reporting HCI as UX. Further, it provides grounding for young researchers making their way in the fast developing world of UX.
Guide to Geometric Algebra in Practice
by Leo Dorst Joan LasenbyThis highly practical Guide to Geometric Algebra in Practice reviews algebraic techniques for geometrical problems in computer science and engineering, and the relationships between them. The topics covered range from powerful new theoretical developments, to successful applications, and the development of new software and hardware tools. Topics and features: provides hands-on review exercises throughout the book, together with helpful chapter summaries; presents a concise introductory tutorial to conformal geometric algebra (CGA) in the appendices; examines the application of CGA for the description of rigid body motion, interpolation and tracking, and image processing; reviews the employment of GA in theorem proving and combinatorics; discusses the geometric algebra of lines, lower-dimensional algebras, and other alternatives to 5-dimensional CGA; proposes applications of coordinate-free methods of GA for differential geometry.
Guide to Graph Algorithms: Sequential, Parallel And Distributed (Texts in Computer Science)
by K ErciyesThis clearly structured textbook/reference presents a detailed and comprehensive review of the fundamental principles of sequential graph algorithms, approaches for NP-hard graph problems, and approximation algorithms and heuristics for such problems. The work also provides a comparative analysis of sequential, parallel and distributed graph algorithms – including algorithms for big data – and an investigation into the conversion principles between the three algorithmic methods.Topics and features: presents a comprehensive analysis of sequential graph algorithms; offers a unifying view by examining the same graph problem from each of the three paradigms of sequential, parallel and distributed algorithms; describes methods for the conversion between sequential, parallel and distributed graph algorithms; surveys methods for the analysis of large graphs and complex network applications; includes full implementation details for the problems presented throughout the text; provides additional supporting material at an accompanying website.This practical guide to the design and analysis of graph algorithms is ideal for advanced and graduate students of computer science, electrical and electronic engineering, and bioinformatics. The material covered will also be of value to any researcher familiar with the basics of discrete mathematics, graph theory and algorithms.
Guide to HTML, JavaScript and PHP
by David R. BrooksThis book enables readers to quickly develop a working knowledge of HTML, JavaScript and PHP. The text emphasizes a hands-on approach to learning and makes extensive use of examples. A detailed science, engineering, or mathematics background is not required to understand the material, making the book ideally suitable for self-study or an introductory course in programming. Features: describes the creation and use of HTML documents; presents fundamental concepts of client-side and server-side programming languages; examines JavaScript and PHP implementation of arrays, built-in and user-defined methods and functions, math capabilities, and input processing with HTML forms; extends programming fundamentals to include reading and writing server-based files, command-line interfaces, and an introduction to GD graphics; appendices include a brief introduction to using a "pseudocode" approach to organizing solutions to computing problems; includes a Glossary and an extensive set of programming exercises.
Guide to ILDJIT
by Simone CampanoniThis book is a guide to getting started with ILDJIT, a compilation framework designed to be both easily extensible and easily configurable. Within this framework, it is possible to build a tool-chain by customizing ILDJIT for specific purposes. Customizations can be used within both static and dynamic compilers already included in the framework without adaptations. Moreover, customizations allow modification of both the behaviors and the characteristics of these compilers to better satisfy the particular need. Currently, ILDJIT is able to translate bytecode programs to generate machine code for both Intel x86 and ARM processors. By relying on ILDJIT technology, more input languages or platforms can be supported. After an introduction to ILDJIT, this guide goes into detail on how to exploit it by extending the framework to match specific requirements. Finally, there is an introduction and discussion of the design choices followed during the authors' years of development efforts towards ILDJIT.
Guide to Industrial Analytics: Solving Data Science Problems for Manufacturing and the Internet of Things (Texts in Computer Science)
by Richard Hill Stuart BerryThis textbook describes the hands-on application of data science techniques to solve problems in manufacturing and the Industrial Internet of Things (IIoT). Monitoring and managing operational performance is a crucial activity for industrial and business organisations. The emergence of low-cost, accessible computing and storage, through Industrial Digital Technologies (IDT) and Industry 4.0, has generated considerable interest in innovative approaches to doing more with data. Data science, predictive analytics, machine learning, artificial intelligence and general approaches to modelling, simulating and visualising industrial systems have often been considered topics only for research labs and academic departments.This textbook debunks the mystique around applied data science and shows readers, using tutorial-style explanations and real-life case studies, how practitioners can develop their own understanding of performance to achieve tangible business improvements. All exercises can be completed with commonly available tools, many of which are free to install and use.Readers will learn how to use tools to investigate, diagnose, propose and implement analytics solutions that will provide explainable results to deliver digital transformation.
Guide to Intelligent Data Analysis
by Frank Klawonn Christian Borgelt Frank Höppner Michael R. BertholdEach passing year bears witness to the development of ever more powerful computers, increasingly fast and cheap storage media, and even higher bandwidth data connections. This makes it easy to believe that we can now - at least in principle - solve any problem we are faced with so long as we only have enough data. Yet this is not the case. Although large databases allow us to retrieve many different single pieces of information and to compute simple aggregations, general patterns and regularities often go undetected. Furthermore, it is exactly these patterns, regularities and trends that are often most valuable. To avoid the danger of "drowning in information, but starving for knowledge" the branch of research known as data analysis has emerged, and a considerable number of methods and software tools have been developed. However, it is not these tools alone but the intelligent application of human intuition in combination with computational power, of sound background knowledge with computer-aided modeling, and of critical reflection with convenient automatic model construction, that results in successful intelligent data analysis projects. Guide to Intelligent Data Analysis provides a hands-on instructional approach to many basic data analysis techniques, and explains how these are used to solve data analysis problems. Topics and features: guides the reader through the process of data analysis, following the interdependent steps of project understanding, data understanding, data preparation, modeling, and deployment and monitoring; equips the reader with the necessary information in order to obtain hands-on experience of the topics under discussion; provides a review of the basics of classical statistics that support and justify many data analysis methods, and a glossary of statistical terms; includes numerous examples using R and KNIME, together with appendices introducing the open source software; integrates illustrations and case-study-style examples to support pedagogical exposition. This practical and systematic textbook/reference for graduate and advanced undergraduate students is also essential reading for all professionals who face data analysis problems. Moreover, it is a book to be used following one's exploration of it. Dr. Michael R. Berthold is Nycomed-Professor of Bioinformatics and Information Mining at the University of Konstanz, Germany. Dr. Christian Borgelt is Principal Researcher at the Intelligent Data Analysis and Graphical Models Research Unit of the European Centre for Soft Computing, Spain. Dr. Frank Höppner is Professor of Information Systems at Ostfalia University of Applied Sciences, Germany. Dr. Frank Klawonn is a Professor in the Department of Computer Science and Head of the Data Analysis and Pattern Recognition Laboratory at Ostfalia University of Applied Sciences, Germany. He is also Head of the Bioinformatics and Statistics group at the Helmholtz Centre for Infection Research, Braunschweig, Germany.
Guide to Intelligent Data Science: How to Intelligently Make Use of Real Data (Texts in Computer Science)
by Frank Klawonn Christian Borgelt Frank Höppner Michael R. Berthold Rosaria SilipoMaking use of data is not anymore a niche project but central to almost every project. With access to massive compute resources and vast amounts of data, it seems at least in principle possible to solve any problem. However, successful data science projects result from the intelligent application of: human intuition in combination with computational power; sound background knowledge with computer-aided modelling; and critical reflection of the obtained insights and results.Substantially updating the previous edition, then entitled Guide to Intelligent Data Analysis, this core textbook continues to provide a hands-on instructional approach to many data science techniques, and explains how these are used to solve real world problems. The work balances the practical aspects of applying and using data science techniques with the theoretical and algorithmic underpinnings from mathematics and statistics. Major updates on techniques and subject coverage (including deep learning) are included.Topics and features: guides the reader through the process of data science, following the interdependent steps of project understanding, data understanding, data blending and transformation, modeling, as well as deployment and monitoring; includes numerous examples using the open source KNIME Analytics Platform, together with an introductory appendix; provides a review of the basics of classical statistics that support and justify many data analysis methods, and a glossary of statistical terms; integrates illustrations and case-study-style examples to support pedagogical exposition; supplies further tools and information at an associated website.This practical and systematic textbook/reference is a “need-to-have” tool for graduate and advanced undergraduate students and essential reading for all professionals who face data science problems. Moreover, it is a “need to use, need to keep” resource following one's exploration of the subject.