"A First Course in Machine Learning by Simon Rogers and Mark Girolami is the best introductory book for ML currently available. It combines rigor and precision with accessibility, starts from a detailed explanation of the basic foundations of Bayesian analysis in the simplest of settings, and goes all the way to the frontiers of the subject such as infinite mixture models, GPs, and MCMC." -Devdatt Dubhashi, Professor, Department of Computer Science and Engineering, Chalmers University, Sweden "This textbook manages to be easier to read than other comparable books in the subject while retaining all the rigorous treatment needed. The new chapters put it at the forefront of the field by covering topics that have become mainstream in machine learning over the last decade." -Daniel Barbara, George Mason University, Fairfax, Virginia, USA "The new edition of A First Course in Machine Learning by Rogers and Girolami is an excellent introduction to the use of statistical methods in machine learning. The book introduces concepts such as mathematical modeling, inference, and prediction, providing 'just in time' the essential background on linear algebra, calculus, and probability theory that the reader needs to understand these concepts." -Daniel Ortiz-Arroyo, Associate Professor, Aalborg University Esbjerg, Denmark "I was impressed by how closely the material aligns with the needs of an introductory course on machine learning, which is its greatest strength...Overall, this is a pragmatic and helpful book, which is well-aligned to the needs of an introductory course and one that I will be looking at for my own students in coming months." -David Clifton, University of Oxford, UK "The first edition of this book was already an excellent introductory text on machine learning for an advanced undergraduate or taught masters level course, or indeed for anybody who wants to learn about an interesting and important field of computer science. The additional chapters of advanced material on Gaussian process, MCMC and mixture modeling provide an ideal basis for practical projects, without disturbing the very clear and readable exposition of the basics contained in the first part of the book." -Gavin Cawley, Senior Lecturer, School of Computing Sciences, University of East Anglia, UK "This book could be used for junior/senior undergraduate students or first-year graduate students, as well as individuals who want to explore the field of machine learning...The book introduces not only the concepts but the underlying ideas on algorithm implementation from a critical thinking perspective." -Guangzhi Qu, Oakland University, Rochester, Michigan, USA

Welcome to the Second International IFIP Entertainment Computing Symposium on st Cultural Computing (ECS 2010), which was part of the 21 IFIP World Computer Congress, held in Brisbane, Australia during September 21-23, 2010. On behalf of the people who made this conference happen, we wish to welcome you to this inter- tional event. The IFIP World Computer Congress has offered an opportunity for researchers and practitioners to present their findings and research results in several prominent areas of computer science and engineering. In the last World Computer Congress, WCC 2008, held in Milan, Italy in September 2008, IFIP launched a new initiative focused on all the relevant issues concerning computing and entertainment. As a - sult, the two-day technical program of the First Entertainment Computing Symposium (ECS 2008) provided a forum to address, explore and exchange information on the state of the art of computer-based entertainment and allied technologies, their design and use, and their impact on society. Based on the success of ECS 2008, at this Second IFIP Entertainment Computing Symposium (ECS 2010), our challenge was to focus on a new area in entertainment computing: cultural computing.

Explains the basic concepts of Python and its role in machine learning Provides comprehensive coverage of feature-engineering including real-time case studies Perceive the structural patterns with reference to data science and statistics and analytics Includes machine learning based structured exercises Appreciates different algorithmic concepts of machine learning including unsupervised, supervised and reinforcement learning

This book provides an overview of the topics of data, sovereignty, and governance with respect to data and online activities through a legal lens and from a cybersecurity perspective. This first chapter explores the concepts of data, ownerships, and privacy with respect to digital media and content, before defining the intersection of sovereignty in law with application to data and digital media content. The authors delve into the issue of digital governance, as well as theories and systems of governance on a state level, national level, and corporate/organizational level. Chapter three jumps into the complex area of jurisdictional conflict of laws and the related issues regarding digital activities in international law, both public and private. Additionally, the book discusses the many technical complexities which underlay the evolution and creation of new law and governance strategies and structures. This includes socio-political, legal, and industrial technical complexities which can apply in these areas. The fifth chapter is a comparative examination of the legal strategies currently being explored by a variety of nations. The book concludes with a discussion about emerging topics which either influence, or are influenced by, data sovereignty and digital governance, such as indigenous data sovereignty, digital human rights and self-determination, artificial intelligence, and global digital social responsibility. Cumulatively, this book provides the full spectrum of information, from foundational principles underlining the described topics, through to the larger, more complex, evolving issues which we can foresee ahead of us.

The book discusses how augmented intelligence can increase the efficiency and speed of diagnosis in healthcare organizations. The concept of augmented intelligence can reflect the enhanced capabilities of human decision-making in clinical settings when augmented with computation systems and methods. It includes real-life case studies highlighting impact of augmented intelligence in health care. The book offers a guided tour of computational intelligence algorithms, architecture design, and applications of learning in healthcare challenges. It presents a variety of techniques designed to represent, enhance, and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics. It also presents specific applications of augmented intelligence in health care, and architectural models and frameworks-based augmented solutions.

This book highlights future research directions and latent solutions by integrating AI and Blockchain 6G networks, comprising computation efficiency, algorithms robustness, hardware development and energy management. This book brings together leading researchers in Academia and industry from diverse backgrounds to deliver to the technical community an outline of emerging technologies, advanced architectures, challenges, open issues and future directions of 6G networks. This book is written for researchers, professionals and students to learn about the integration of technologies such as AI and Blockchain into 6G network and communications. This book addresses the topics such as consensus protocol, architecture, intelligent dynamic resource management, security and privacy in 6G to integrate AI and Blockchain and new real-time application with further research opportunities.

This book provides a comprehensive methodology to measure systemic risk in many of its facets and dimensions based on state-of-the-art risk assessment methods. Systemic risk has gained attention in the public eye since the collapse of Lehman Brothers in 2008. The bankruptcy of the fourth-biggest bank in the USA raised questions whether banks that are allowed to become "too big to fail" and "too systemic to fail" should carry higher capital surcharges on their size and systemic importance. The Global Financial Crisis of 2008-2009 was followed by the Sovereign Debt Crisis in the euro area that saw the first Eurozone government de facto defaulting on its debt and prompted actions at international level to stem further domino and cascade effects to other Eurozone governments and banks. Against this backdrop, a careful measurement of systemic risk is of utmost importance for the new capital regulation to be successful and for sovereign risk to remain in check. Most importantly, the book introduces a number of systemic fragility indicators for banks and sovereigns that can help to assess systemic risk and the impact of macroprudential and microprudential policies.

Education and Technology for a Better World was the main theme for WCCE 2009. The conference highlights and explores different perspectives of this theme, covering all levels of formal education as well as informal learning and societal aspects of education. The conference was open to everyone involved in education and training. Additionally players from technological, societal, business and political fields outside education were invited to make relevant contributions within the theme: Education and Technology for a Better World. For several years the WCCE (World Conference on Computers in Education) has brought benefits to the fields of computer science and computers and education as well as to their communities. The contributions at WCCE include research projects and good practice presented in different formats from full papers to posters, demonstrations, panels, workshops and symposiums. The focus is not only on presentations of accepted contributions but also on discussions and input from all participants. The main goal of these conferences is to provide a forum for the discussion of ideas in all areas of computer science and human learning. They create a unique environment in which researchers and practitioners in the fields of computer science and human learning can interact, exchanging theories, experiments, techniques, applications and evaluations of initiatives supporting new developments that are potentially relevant for the development of these fields. They intend to serve as reference guidelines for the research community.

Agricultural systems are uniquely complex systems, given that agricultural systems are parts of natural and ecological systems. Those aspects bring in a substantial degree of uncertainty in system operation. Also, impact factors, such as weather factors, are critical in agricultural systems but these factors are uncontrollable in system management. Modern agriculture has been evolving through precision agriculture beginning in the late 1980s and biotechnological innovations in the early 2000s. Precision agriculture implements site-specific crop production management by integrating agricultural mechanization and information technology in geographic information system (GIS), global navigation satellite system (GNSS), and remote sensing. Now, precision agriculture is set to evolve into smart agriculture with advanced systematization, informatization, intelligence and automation. From precision agriculture to smart agriculture, there is a substantial amount of specific control and communication problems that have been investigated and will continue to be studied. In this book, the core ideas and methods from control problems in agricultural production systems are extracted, and a system view of agricultural production is formulated for the analysis and design of management strategies to control and optimize agricultural production systems while exploiting the intrinsic feedback information-exchanging mechanisms. On this basis, the theoretical framework of agricultural cybernetics is established to predict and control the behavior of agricultural production systems through control theory.

Although an emerging technology, blockchain is here to stay. Since its inception, imaginative thinkers have identified new ways for this powerful technology to bring innovative solutions to problems in the business world. Considered by many as an extreme and disruptive change, how can business leaders overcome resistance to the implementation of blockchain solutions and maximize its potential? The Emerald Handbook of Blockchain for Business equips academics, practitioners, and students with a broad understanding of the cutting-edge developments and applications of emerging blockchain technology. Covering the basic concepts while also showcasing practical applications in intricate real-world situations, this handbook bridges the gap between theory and practice, providing a useful balance of detailed and user-friendly coverage. Facilitating readers with a working knowledge of how blockchain functions and integrates within the business world, this handbook is essential reading for academics looking for a springboard for further research and practitioners needing a go-to resource for navigating the implementation of this fast-moving new technology.

This book constitutes the proceedings of the 14th IFIP WG 11.12 International Symposium on Human Aspects of Information Security and Assurance, HAISA 2020, held in Mytilene, Lesbos, Greece, in July 2020.* The 27 full papers presented in this volume were carefully reviewed and selected from 43 submissions. They are organized in the following topical sections: privacy and COVID-19; awareness and training; social engineering; security behavior; education; end-user security; usable security; security policy; and attitudes and perceptions. *The symposium was held virtually due to the COVID-19 pandemic.

Most of the papers in this volume were first presented at the Workshop on Cross-Linguistic Information Retrieval that was held August 22, 1996 dur ing the SIGIR'96 Conference. Alan Smeaton of Dublin University and Paraic Sheridan of the ETH, Zurich, were the two other members of the Scientific Committee for this workshop. SIGIR is the Association for Computing Ma chinery (ACM) Special Interest Group on Information Retrieval, and they have held conferences yearly since 1977. Three additional papers have been added: Chapter 4 Distributed Cross-Lingual Information retrieval describes the EMIR retrieval system, one of the first general cross-language systems to be implemented and evaluated; Chapter 6 Mapping Vocabularies Using Latent Semantic Indexing, which originally appeared as a technical report in the Lab oratory for Computational Linguistics at Carnegie Mellon University in 1991, is included here because it was one of the earliest, though hard-to-find, publi cations showing the application of Latent Semantic Indexing to the problem of cross-language retrieval; and Chapter 10 A Weighted Boolean Model for Cross Language Text Retrieval describes a recent approach to solving the translation term weighting problem, specific to Cross-Language Information Retrieval. Gregory Grefenstette CONTRIBUTORS Lisa Ballesteros David Hull W, Bruce Croft Gregory Grefenstette Center for Intelligent Xerox Research Centre Europe Information Retrieval Grenoble Laboratory Computer Science Department University of Massachusetts Thomas K. Landauer Department of Psychology Mark W. Davis and Institute of Cognitive Science Computing Research Lab University of Colorado, Boulder New Mexico State University Michael L. Littman Bonnie J."

Safety-Critical Real-Time Systems brings together in one place important contributions and up-to-date research results in this fast moving area. Safety-Critical Real-Time Systems serves as an excellent reference, providing insight into some of the most challenging research issues in the field.

The benefits of distributed computing are evidenced by the increased functionality, retrieval capability, and reliability it provides for a number of networked applications. The growth of the Internet into a critical part of daily life has encouraged further study on how data can better be transferred, managed, and evaluated in an ever-changing online environment. Advancements in Distributed Computing and Internet Technologies: Trends and Issues compiles recent research trends and practical issues in the fields of distributed computing and Internet technologies. The book provides advancements on emerging technologies that aim to support the effective design and implementation of service-oriented networks, future Internet environments, and building management frameworks. Research on Internet-based systems design, wireless sensor networks and their application, and next generation distributed systems will inform graduate students, researchers, academics, and industry practitioners of new trends and vital research in this evolving discipline.

This book constitutes the refereed proceedings of the 14th IFIP TC 9 International Conference on Human Choice and Computers, HCC14 2020, which was supposed take place in Tokyo, Japan, in September 2020, but the conference was cancelled due to the COVID-19 crisis.The 31 revised full papers presented were carefully reviewed and selected from 55 submissions. The papers deal with the constantly evolving intimate relationship between humans and technology. They are organized in the following sections: ethical and legal considerations in a data-driven society; the data-driven society; peace and war; our digital lives; individuals in data-driven society; and gender, diversity and ICT.

The Digital Humanities have arrived at a moment when digital Big Data is becoming more readily available, opening exciting new avenues of inquiry but also new challenges. This pioneering book describes and demonstrates the ways these data can be explored to construct cultural heritage knowledge, for research and in teaching and learning. It helps humanities scholars to grasp Big Data in order to do their work, whether that means understanding the underlying algorithms at work in search engines, or designing and using their own tools to process large amounts of information.Demonstrating what digital tools have to offer and also what 'digital' does to how we understand the past, the authors introduce the many different tools and developing approaches in Big Data for historical and humanistic scholarship, show how to use them, what to be wary of, and discuss the kinds of questions and new perspectives this new macroscopic perspective opens up. Authored 'live' online with ongoing feedback from the wider digital history community, Exploring Big Historical Data breaks new ground and sets the direction for the conversation into the future. It represents the current state-of-the-art thinking in the field and exemplifies the way that digital work can enhance public engagement in the humanities.Exploring Big Historical Data should be the go-to resource for undergraduate and graduate students confronted by a vast corpus of data, and researchers encountering these methods for the first time. It will also offer a helping hand to the interested individual seeking to make sense of genealogical data or digitized newspapers, and even the local historical society who are trying to see the value in digitizing their holdings.The companion website to Exploring Big Historical Data can be found at www.themacroscope.org/. On this site you will find code, a discussion forum, essays, and datafiles that accompany this book.

This book focuses on techniques that can be applied at the physical and data-link layers of communication systems in order to secure transmissions against eavesdroppers. Topics ranging from information theory-based security to coding for security and cryptography are discussed, with presentation of cutting-edge research and innovative results from leading researchers. The characteristic feature of all the contributions is their relevance for practical embodiments: detailed consideration is given to applications of security principles to a variety of widely used communication techniques such as multiantenna systems, ultra-wide band communication systems, power line communications, and quantum key distribution techniques. A further distinctive aspect is the attention paid to both unconditional and computational security techniques, providing a bridge between two usually distinct worlds. The book comprises extended versions of contributions delivered at the Workshop on Communication Security, held in Ancona, Italy, in September 2014 within the framework of the research project "Enhancing Communication Security by Cross-layer Physical and Data-link Techniques", funded by the Italian Ministry of Education, Universities, and Research.

Explains concepts of Internet of Everything problems, research challenge goals, and vision in smart cities Based on the most recent innovations, and covering the major challenges in smart cities, between IoT and Big Data Examines security issues and challenges related to data-intensive advances in IoT Addresses the total information science challenges in Internet of Everything enabled technologies Covers the exploring and creating IoT environment related self-adaptive systems

This volume offers the reader a systematic and throughout account of branches of logic instrumental for computer science, data science and artificial intelligence. Addressed in it are propositional, predicate, modal, epistemic, dynamic, temporal logics as well as applicable in data science many-valued logics and logics of concepts (rough logics). It offers a look into second-order logics and approximate logics of parts. The book concludes with appendices on set theory, algebraic structures, computability, complexity, MV-algebras and transition systems, automata and formal grammars. By this composition of the text, the reader obtains a self-contained exposition that can serve as the textbook on logics and relevant disciplines as well as a reference text.

Recent advances in computing, communication, and data storage have led to an increasing number of large digital libraries publicly available on the Internet. In addition to alphanumeric data, other modalities, including video play an important role in these libraries. Ordinary techniques will not retrieve required information from the enormous mass of data stored in digital video libraries. Instead of words, a video retrieval system deals with collections of video records. Therefore, the system is confronted with the problem of video understanding. The system gathers key information from a video in order to allow users to query semantics instead of raw video data or video features. Users expect tools that automatically understand and manipulate the video content in the same structured way as a traditional database manages numeric and textual data. Consequently, content-based search and retrieval of video data becomes a challenging and important problem.
This book focuses particularly on content-based video retrieval. After addressing basic concepts and techniques in the field, Content-Based Video Retrieval: A Database Perspective concentrates on the semantic gap problem, i.e., the problem of inferring semantics from raw video data, as the main problem of content-based video retrieval. This book identifies and proposes the integrated use of three different techniques to bridge the semantic gap, namely, spatio-temporal formalization methods, hidden Markov models, and dynamic Bayesian networks. As the problem is approached from a database perspective, the emphasis evolves from a database management system into a video database management system. This system allows a user to retrievethe desired video sequence among voluminous amounts of video data in an efficient and semantically meaningful way. This book also presents a modeling framework and a prototype of a content-based video management system that integrates the three methods and provides efficient, flexible, and scalable content-based video retrieval. The proposed approach is validated in the domain of sport videos for which some experimental results are presented.
Content-Based Video Retrieval: A Database Perspective is designed for a professional audience, composed of researchers and practitioners in industry. This book is also suitable as a secondary text for graduate-level students in computer science and electrical engineering.

The emerging field of Data Science has had a large impact on science and society. This book explores how one distinguishing feature of Data Science - its focus on data collected from social and environmental contexts within which learners often find themselves deeply embedded - suggests serious implications for learning and education. Drawing from theories of learning and identity development in the learning sciences, this volume investigates the impacts of these complex relationships on how learners think about, use, and share data, including their understandings of data in light of history, race, geography, and politics. More than just using 'real world examples' to motivate students to work with data, this book demonstrates how learners' relationships to data shape how they approach those data with agency, as part of their social and cultural lives. Together, the contributions offer a vision of how the learning sciences can contribute to a more expansive, socially aware, and transformative Data Science Education. The chapters in this book were originally published as a special issue of the Journal of the Learning Sciences.

Learn how to create, train, and tweak large language models (LLMs) by building one from the ground up!

In Build a Large Language Model (from Scratch) bestselling author Sebastian Raschka guides you step by step through creating your own LLM. Each stage is explained with clear text, diagrams, and examples. You’ll go from the initial design and creation, to pretraining on a general corpus, and on to fine-tuning for specific tasks.

Build a Large Language Model (from Scratch) teaches you how to:

• Plan and code all the parts of an LLM
• Prepare a dataset suitable for LLM training
• Fine-tune LLMs for text classification and with your own data
• Use human feedback to ensure your LLM follows instructions
• Load pretrained weights into an LLM

Build a Large Language Model (from Scratch) takes you inside the AI black box to tinker with the internal systems that power generative AI. As you work through each key stage of LLM creation, you’ll develop an in-depth understanding of how LLMs work, their limitations, and their customization methods. Your LLM can be developed on an ordinary laptop, and used as your own personal assistant.

"In what is certain to be a seminal work on metadata, John Horodyski masterfully affirms the value of metadata while providing practical examples of its role in our personal and professional lives. He does more than tell us that metadata matters-he vividly illustrates why it matters." -Patricia C. Franks, PhD, CA, CRM, IGP, CIGO, FAI, President, NAGARA, Professor Emerita, San Jose State University, USA If data is the language upon which our modern society will be built, then metadata will be its grammar, the construction of its meaning, the building for its content, and the ability to understand what data can be for us all. We are just starting to bring change into the management of the data that connects our experiences. Metadata Matters explains how metadata is the foundation of digital strategy. If digital assets are to be discovered, they want to be found. The path to good metadata design begins with the realization that digital assets need to be identified, organized, and made available for discovery. This book explains how metadata will help ensure that an organization is building the right system for the right users at the right time. Metadata matters and is the best chance for a return on investment on digital assets and is also a line of defense against lost opportunities. It matters to the digital experience of users. It helps organizations ensure that users can identify, discover, and experience their brands in the ways organizations intend. It is a necessary defense, which this book shows how to build.

Data analytics underpin our modern data-driven economy. This textbook explains the relevance of data analytics at the firm and industry levels, tracing the evolution and key components of the field, and showing how data analytics insights can be leveraged for business results. The first section of the text covers key topics such as data analytics tools, data mining, business intelligence, customer relationship management, and cybersecurity. The chapters then take an industry focus, exploring how data analytics can be used in particular settings to strengthen business decision-making. A range of sectors are examined, including financial services, accounting, marketing, sport, health care, retail, transport, and education. With industry case studies, clear definitions of terminology, and no background knowledge required, this text supports students in gaining a solid understanding of data analytics and its practical applications. PowerPoint slides, a test bank of questions, and an instructor's manual are also provided as online supplements. This will be a valuable text for undergraduate level courses in data analytics, data mining, business intelligence, and related areas.

Peer-to-peer (P2P) technology, or peer computing, is a paradigm that is viewed as a potential technology for redesigning distributed architectures and, consequently, distributed processing. Yet the scale and dynamism that characterize P2P systems demand that we reexamine traditional distributed technologies. A paradigm shift that includes self-reorganization, adaptation and resilience is called for. On the other hand, the increased computational power of such networks opens up completely new applications, such as in digital content sharing, scientific computation, gaming, or collaborative work environments.

In this book, Vu, Lupu and Ooi present the technical challenges offered by P2P systems, and the means that have been proposed to address them. They provide a thorough and comprehensive review of recent advances on routing and discovery methods; load balancing and replication techniques; security, accountability and anonymity, as well as trust and reputation schemes; programming models and P2P systems and projects. Besides surveying existing methods and systems, they also compare and evaluate some of the more promising schemes.

The need for such a book is evident. It provides a single source for practitioners, researchers and students on the state of the art. For practitioners, this book explains best practice, guiding selection of appropriate techniques for each application. For researchers, this book provides a foundation for the development of new and more effective methods. For students, it is an overview of the wide range of advanced techniques for realizing effective P2P systems, and it can easily be used as a text for an advanced course on Peer-to-Peer Computing and Technologies, or as a companion text for courses on various subjects, such as distributed systems, and grid and cluster computing.