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Statistical Reinforcement Learning Modern Machine Learning Approaches

Statistical Reinforcement Learning Modern Machine Learning Approaches

Reinforcement learning is a mathematical framework for developing computer agents that can learn an optimal behavior by relating generic reward signals with its past actions. With numerous successful applications in business intelligence plant control and gaming the RL framework is ideal for decision making in unknown environments with large amounts of data. Supplying an up-to-date and accessible introduction to the field Statistical Reinforcement Learning: Modern Machine Learning Approaches presents fundamental concepts and practical algorithms of statistical reinforcement learning from the modern machine learning viewpoint. It covers various types of RL approaches including model-based and model-free approaches policy iteration and policy search methods. Covers the range of reinforcement learning algorithms from a modern perspectiveLays out the associated optimization problems for each reinforcement learning scenario coveredProvides thought-provoking statistical treatment of reinforcement learning algorithmsThe book covers approaches recently introduced in the data mining and machine learning fields to provide a systematic bridge between RL and data mining/machine learning researchers. It presents state-of-the-art results including dimensionality reduction in RL and risk-sensitive RL. Numerous illustrative examples are included to help readers understand the intuition and usefulness of reinforcement learning techniques. This book is an ideal resource for graduate-level students in computer science and applied statistics programs as well as researchers and engineers in related fields. | Statistical Reinforcement Learning Modern Machine Learning Approaches

GBP 44.99
1

Modern Survey Sampling

Modern Survey Sampling

Starting from the preliminaries and ending with live examples Modern Survey Sampling details what a sample can communicate about an unknowable aggregate in a real situation. The author lucidly develops and presents numerous approaches. He details recent developments and explores fresh and unseen problems hitting upon possible solutions. The text covers current research output in a student-friendly manner with attractive illustrations. It introduces sampling and discusses how to select a sample for which a selection-probability is specified to prescribe its performance characteristics. The author then explains how to examine samples with varying probabilities to derive profits. He then examines how to use partial segments to make reasonable guesses about a sample’s behavior and assess the elements of discrepancies. Including case studies exercises and solutions the book highlights special survey techniques needed to capture trustworthy data and put it to intelligent use. It then discusses the model-assisted approach and network sampling before moving on to speculating about random processes. The author draws on his extensive teaching experience to create a textbook that gives your students a thorough grounding in the technologies of survey sampling and modeling and also provides you with the tools to teach them.

GBP 59.99
1

Modern Data Science with R

Modern Data Science with R

From a review of the first edition: Modern Data Science with R… is rich with examples and is guided by a strong narrative voice. What’s more it presents an organizing framework that makes a convincing argument that data science is a course distinct from applied statistics (The American Statistician). Modern Data Science with R is a comprehensive data science textbook for undergraduates that incorporates statistical and computational thinking to solve real-world data problems. Rather than focus exclusively on case studies or programming syntax this book illustrates how statistical programming in the state-of-the-art R/RStudio computing environment can be leveraged to extract meaningful information from a variety of data in the service of addressing compelling questions. The second edition is updated to reflect the growing influence of the tidyverse set of packages. All code in the book has been revised and styled to be more readable and easier to understand. New functionality from packages like sf purrr tidymodels and tidytext is now integrated into the text. All chapters have been revised and several have been split re-organized or re-imagined to meet the shifting landscape of best practice.

GBP 82.99
1

Operating Systems Evolutionary Concepts and Modern Design Principles

Operating Systems Evolutionary Concepts and Modern Design Principles

This text demystifies the subject of operating systems by using a simple step-by-step approach from fundamentals to modern concepts of traditional uniprocessor operating systems in addition to advanced operating systems on various multiple-processor platforms and also real-time operating systems (RTOSs). While giving insight into the generic operating systems of today its primary objective is to integrate concepts techniques and case studies into cohesive chapters that provide a reasonable balance between theoretical design issues and practical implementation details. It addresses most of the issues that need to be resolved in the design and development of continuously evolving rich diversified modern operating systems and describes successful implementation approaches in the form of abstract models and algorithms. This book is primarily intended for use in undergraduate courses in any discipline and also for a substantial portion of postgraduate courses that include the subject of operating systems. It can also be used for self-study. Key Features • Exhaustive discussions on traditional uniprocessor-based generic operating systems with figures tables and also real-life implementations of Windows UNIX Linux and to some extent Sun Solaris. • Separate chapter on security and protection: a grand challenge in the domain of today’s operating systems describing many different issues including implementation in modern operating systems like UNIX Linux and Windows. • Separate chapter on advanced operating systems detailing major design issues and salient features of multiple-processor-based operating systems including distributed operating systems. Cluster architecture; a low-cost base substitute for true distributed systems is explained including its classification merits and drawbacks. • Separate chapter on real-time operating systems containing fundamental topics useful concepts and major issues as well as a few different types of real-life implementations. • Online Support Material is provided to negotiate acute page constraint which is exclusively a part and parcel of the text delivered in this book containing the chapter-wise/topic-wise detail explanation with representative figures of many important areas for the completeness of the narratives. | Operating Systems Evolutionary Concepts and Modern Design Principles

GBP 150.00
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A Modern Introduction to Linear Algebra

A Modern Introduction to Linear Algebra

Useful Concepts and Results at the Heart of Linear AlgebraA one- or two-semester course for a wide variety of students at the sophomore/junior undergraduate levelA Modern Introduction to Linear Algebra provides a rigorous yet accessible matrix-oriented introduction to the essential concepts of linear algebra. Concrete easy-to-understand examples motivate the theory. The book first discusses vectors Gaussian elimination and reduced row echelon forms. It then offers a thorough introduction to matrix algebra including defining the determinant naturally from the PA=LU factorization of a matrix. The author goes on to cover finite-dimensional real vector spaces infinite-dimensional spaces linear transformations and complex vector spaces. The final chapter presents Hermitian and normal matrices as well as quadratic forms. Taking a computational algebraic and geometric approach to the subject this book provides the foundation for later courses in higher mathematics. It also shows how linear algebra can be used in various areas of application. Although written in a pencil and paper manner the text offers ample opportunities to enhance learning with calculators or computer usage. Solutions manual available for qualifying instructors

GBP 59.99
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Parallel Programming for Modern High Performance Computing Systems

Parallel Programming for Modern High Performance Computing Systems

In view of the growing presence and popularity of multicore and manycore processors accelerators and coprocessors as well as clusters using such computing devices the development of efficient parallel applications has become a key challenge to be able to exploit the performance of such systems. This book covers the scope of parallel programming for modern high performance computing systems. It first discusses selected and popular state-of-the-art computing devices and systems available today These include multicore CPUs manycore (co)processors such as Intel Xeon Phi accelerators such as GPUs and clusters as well as programming models supported on these platforms. It next introduces parallelization through important programming paradigms such as master-slave geometric Single Program Multiple Data (SPMD) and divide-and-conquer. The practical and useful elements of the most popular and important APIs for programming parallel HPC systems are discussed including MPI OpenMP Pthreads CUDA OpenCL and OpenACC. It also demonstrates through selected code listings how selected APIs can be used to implement important programming paradigms. Furthermore it shows how the codes can be compiled and executed in a Linux environment. The book also presents hybrid codes that integrate selected APIs for potentially multi-level parallelization and utilization of heterogeneous resources and it shows how to use modern elements of these APIs. Selected optimization techniques are also included such as overlapping communication and computations implemented using various APIs. Features:Discusses the popular and currently available computing devices and cluster systemsIncludes typical paradigms used in parallel programsExplores popular APIs for programming parallel applicationsProvides code templates that can be used for implementation of paradigmsProvides hybrid code examples allowing multi-level parallelizationCovers the optimization of parallel programs

GBP 44.99
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Innovative Strategies Statistical Solutions and Simulations for Modern Clinical Trials

Innovative Strategies Statistical Solutions and Simulations for Modern Clinical Trials

This is truly an outstanding book. [It] brings together all of the latest research in clinical trials methodology and how it can be applied to drug development…. Chang et al provide applications to industry-supported trials. This will allow statisticians in the industry community to take these methods seriously. Jay Herson Johns Hopkins UniversityThe pharmaceutical industry's approach to drug discovery and development has rapidly transformed in the last decade from the more traditional Research and Development (R & D) approach to a more innovative approach in which strategies are employed to compress and optimize the clinical development plan and associated timelines. However these strategies are generally being considered on an individual trial basis and not as part of a fully integrated overall development program. Such optimization at the trial level is somewhat near-sighted and does not ensure cost time or development efficiency of the overall program. This book seeks to address this imbalance by establishing a statistical framework for overall/global clinical development optimization and providing tactics and techniques to support such optimization including clinical trial simulations. Provides a statistical framework for achieve global optimization in each phase of the drug development process. Describes specific techniques to support optimization including adaptive designs precision medicine survival-endpoints dose finding and multiple testing. Gives practical approaches to handling missing data in clinical trials using SAS. Looks at key controversial issues from both a clinical and statistical perspective. Presents a generous number of case studies from multiple therapeutic areas that help motivate and illustrate the statistical methods introduced in the book. Puts great emphasis on software implementation of the statistical methods with multiple examples of software code (both SAS and R). It is important for statisticians to possess a deep knowledge of the drug development process beyond statistical considerations. For these reasons this book incorporates both statistical and clinical/medical perspectives. | Innovative Strategies Statistical Solutions and Simulations for Modern Clinical Trials

GBP 44.99
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Computational Mathematics An introduction to Numerical Analysis and Scientific Computing with Python

Computational Mathematics An introduction to Numerical Analysis and Scientific Computing with Python

This textbook is a comprehensive introduction to computational mathematics and scientific computing suitable for undergraduate and postgraduate courses. It presents both practical and theoretical aspects of the subject as well as advantages and pitfalls of classical numerical methods alongside with computer code and experiments in Python. Each chapter closes with modern applications in physics engineering and computer science. Features: No previous experience in Python is required. Includes simplified computer code for fast-paced learning and transferable skills development. Includes practical problems ideal for project assignments and distance learning. Presents both intuitive and rigorous faces of modern scientific computing. Provides an introduction to neural networks and machine learning. | Computational Mathematics An introduction to Numerical Analysis and Scientific Computing with Python

GBP 99.99
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Handbook of Survival Analysis

Handbook of Survival Analysis

Handbook of Survival Analysis presents modern techniques and research problems in lifetime data analysis. This area of statistics deals with time-to-event data that is complicated by censoring and the dynamic nature of events occurring in time. With chapters written by leading researchers in the field the handbook focuses on advances in survival analysis techniques covering classical and Bayesian approaches. It gives a complete overview of the current status of survival analysis and should inspire further research in the field. Accessible to a wide range of readers the book provides: An introduction to various areas in survival analysis for graduate students and novices A reference to modern investigations into survival analysis for more established researchers A text or supplement for a second or advanced course in survival analysis A useful guide to statistical methods for analyzing survival data experiments for practicing statisticians

GBP 66.99
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From Computing to Computational Thinking

From Computing to Computational Thinking

Computational Thinking (CT) involves fundamental concepts and reasoning distilled from computer science and other computational sciences which become powerful general mental tools for solving problems increasing efficiency reducing complexity designing procedures or interacting with humans and machines. An easy-to-understand guidebook From Computing to Computational Thinking gives you the tools for understanding and using CT. It does not assume experience or knowledge of programming or of a programming language but explains concepts and methods for CT with clarity and depth. Successful applications in diverse disciplines have shown the power of CT in problem solving. The book uses puzzles games and everyday examples as starting points for discussion and for connecting abstract thinking patterns to real-life situations. It provides an interesting and thought-provoking way to gain general knowledge about modern computing and the concepts and thinking processes underlying modern digital technologies.

GBP 180.00
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Cloud IoT Systems for Smart Agricultural Engineering

Cloud IoT Systems for Smart Agricultural Engineering

Agriculture plays a vital role in a country’s growth. Modern-day technologies drive every domain toward smart systems. The use of traditional agricultural procedures to satisfy modern-day requirements is a challenging task. Cloud IoT Systems for Smart Agricultural Engineering provides substantial coverage of various challenges of the agriculture domain through modern technologies such as the Internet of Things (IoT) cloud computing and many more. This book offers various state-of-the-art procedures to be deployed in a wide range of agricultural activities. The concepts are discussed with the necessary implementations and clear examples. Necessary illustrations are depicted in the chapters to ensure the effective delivery of the proposed concepts. It presents the rapid advancement of the technologies in the existing agricultural model by applying the cloud IoT techniques. A wide variety of novel architectural solutions are discussed in various chapters of this book. This book provides comprehensive coverage of the most essential topics including: New approaches on urban and vertical farming Smart crop management for Indian farmers Smart livestock management Precision agriculture using geographical information systems Machine learning techniques combined with IoT for smart agriculture Effective use of drones in smart agriculture This book provides solutions for the diverse domain of problems in agricultural engineering. It can be used at the basic and intermediary levels for agricultural science and engineering graduate students researchers and practitioners.

GBP 145.00
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Handbook of Item Response Theory Three Volume Set

Handbook of Item Response Theory Three Volume Set

Drawing on the work of 75 internationally acclaimed experts in the field Handbook of Item Response Theory Three-Volume Set presents all major item response models classical and modern statistical tools used in item response theory (IRT) and major areas of applications of IRT in educational and psychological testing medical diagnosis of patient-reported outcomes and marketing research. It also covers CRAN packages WinBUGS Bilog MG Multilog Parscale IRTPRO Mplus GLLAMM Latent Gold and numerous other software tools. A full update of editor Wim J. van der Linden and Ronald K. Hambleton’s classic Handbook of Modern Item Response Theory this handbook has been expanded from 28 chapters to 85 chapters in three volumes. The three volumes are thoroughly edited and cross-referenced with uniform notation format and pedagogical principles across all chapters. Each chapter is self-contained and deals with the latest developments in IRT. | Handbook of Item Response Theory Three Volume Set

GBP 140.00
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Statistical Methods in Health Disparity Research

Statistical Methods in Health Disparity Research

A health disparity refers to a higher burden of illness injury disability or mortality experienced by one group relative to others attributable to multiple factors including socioeconomic status environmental factors insufficient access to health care individual risk factors and behaviors and inequalities in education. These disparities may be due to many factors including age income and race. Statistical Methods in Health Disparity Research will focus on their estimation ranging from classical approaches including the quantification of a disparity to more formal modeling to modern approaches involving more flexible computational approaches. Features: Presents an overview of methods and applications of health disparity estimation First book to synthesize research in this field in a unified statistical framework Covers classical approaches and builds to more modern computational techniques Includes many worked examples and case studies using real data Discusses available software for estimation The book is designed primarily for researchers and graduate students in biostatistics data science and computer science. It will also be useful to many quantitative modelers in genetics biology sociology and epidemiology.

GBP 90.00
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Design and Analysis of Experiments and Observational Studies using R

Design and Analysis of Experiments and Observational Studies using R

Introduction to Design and Analysis of Scientific Studies exposes undergraduate and graduate students to the foundations of classical experimental design and observational studies through a modern framework - The Rubin Causal Model. A causal inference framework is important in design data collection and analysis since it provides a framework for investigators to readily evaluate study limitations and draw appropriate conclusions. R is used to implement designs and analyse the data collected. Features: Classical experimental design with an emphasis on computation using tidyverse packages in R. Applications of experimental design to clinical trials A/B testing and other modern examples. Discussion of the link between classical experimental design and causal inference. The role of randomization in experimental design and sampling in the big data era. Exercises with solutions. Instructor slides in RMarkdown a new R package will be developed to be used with book and a bookdown version of the book will be freely available. The proposed book will emphasize ethics communication and decision making as part of design data analysis and statistical thinking. | Design and Analysis of Experiments and Observational Studies using R

GBP 82.99
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Equity-Linked Life Insurance Partial Hedging Methods

Equity-Linked Life Insurance Partial Hedging Methods

This book focuses on the application of the partial hedging approach from modern math finance to equity-linked life insurance contracts. It provides an accessible up-to-date introduction to quantifying financial and insurance risks. The book also explains how to price innovative financial and insurance products from partial hedging perspectives. Each chapter presents the problem the mathematical formulation theoretical results derivation details numerical illustrations and references to further reading. | Equity-Linked Life Insurance Partial Hedging Methods

GBP 44.99
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Clean Numerical Simulation

Clean Numerical Simulation

This book describes the basic principles of Clean Numerical Simulation (CNS) proposed by the author in 2009 as well as several of its applications. Unlike conventional algorithms CNS gives in a sufficiently long interval of time a convergent chaotic trajectory whose numerical noise is much lower than the true physical solution so that one can gain accurately. Thus CNS provides for the first time an ability to check statistics stability of chaos leading to a completely new concept of ultra-chaos which has both trajectory instability and statistics instability and thus is of a higher disorder. Notably it is impossible to repeat experimental results of ultra-chaos even in the statistical sense. However the reproducibility of physical experiments forms a cornerstone for modern science. Thus ultra-chaos reveals an incompleteness of the modern science paradigm. In addition it also reveals statistics stability as a precondition for use of conventional algorithms including direct numerical simulation (DNS). In Clean Numerical Simulation several conjectures and open problems are proposed including a modified fourth Clay millennium problem. Indeed CNS opens the door for us to enter the clean numerical world of chaos and turbulence.

GBP 74.99
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Cure Models Methods Applications and Implementation

Cure Models Methods Applications and Implementation

Cure Models: Methods Applications and Implementation is the first book in the last 25 years that provides a comprehensive and systematic introduction to the basics of modern cure models including estimation inference and software. This book is useful for statistical researchers and graduate students and practitioners in other disciplines to have a thorough review of modern cure model methodology and to seek appropriate cure models in applications. The prerequisites of this book include some basic knowledge of statistical modeling survival models and R and SAS for data analysis. The book features real-world examples from clinical trials and population-based studies and a detailed introduction to R packages SAS macros and WinBUGS programs to fit some cure models. The main topics covered include the foundation of statistical estimation and inference of cure models for independent and right-censored survival data cure modeling for multivariate recurrent-event and competing-risks survival data and joint modeling with longitudinal data statistical testing for the existence and difference of cure rates and sufficient follow-up new developments in Bayesian cure models applications of cure models in public health research and clinical trials. | Cure Models Methods Applications and Implementation

GBP 35.99
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Statistical Regression and Classification From Linear Models to Machine Learning

Statistical Regression and Classification From Linear Models to Machine Learning

This text provides a modern introduction to regression and classification with an emphasis on big data and R. Each chapter is partitioned into a main body section and an extras section. The main body uses math stat very sparingly and always in the context of something concrete which means that readers can skip the math stat content entirely if they wish. The extras section is for those who feel comfortable with analysis using math stat. | Statistical Regression and Classification From Linear Models to Machine Learning

GBP 66.99
1

Case Studies in Innovative Clinical Trials

Case Studies in Innovative Clinical Trials

Drug development is a strictly regulated area. As such marketing approval of a new drug depends heavily if not exclusively on evidence generated from clinical trials. Drug development has seen tremendous innovation in science and technology that has revolutionized the treatment of some diseases. And yet the statistical design and practical conduct of the clinical trials used to test new therapeutics for safety and efficacy have changed very little over the decades. Our approach to clinical trials is steeped in convention and tradition. The large fixed randomized controlled trial methods that have been the gold standard are well understood and expected by many trial stakeholders. However this approach is not well suited to all aspects of modern drug development and the current competitive landscape. We now see new therapies that target a small fraction of the patient population rare diseases with high unmet medical needs and pediatric populations that must wait for years for new drug approvals from the time that therapies are approved in adults. Large randomized clinical trials are at best inefficient and at worst completely infeasible in many modern clinical settings. Advances in technology and data infrastructure call for innovations in clinical trial design. Despite advances in statistical methods the availability of information and computing power the actual experience with innovative design in clinical trials across industry and academia is limited. This book will be an important showcase of the potential for these innovative designs in modern drug development and will be an important resource to guide those who wish to undertake them for themselves. This book is ideal for professionals in the pharmaceutical industry and regulatory agencies but it will also be useful to academic researchers faculty members and graduate students in statistics biostatistics public health and epidemiology due to its focus on innovation. Key Features: Is written by pharmaceutical industry experts academic researchers and regulatory reviewers; this is the first book providing a comprehensive set of case studies related to statistical methodology implementation regulatory considerations and communication of complex innovative trial design Has a broad appeal to a multitude of readers across academia industry and regulatory agencies Each contribution is a practical case study that can speak to the benefits of an innovative approach but also balance that with the real-life challenges encountered A complete understanding of what is actually being done in modern clinical trials will broaden the reader’s capabilities and provide examples to first mimic and then customize and expand upon when exploring these ideas on their own | Case Studies in Innovative Clinical Trials

GBP 130.00
1

Meta-analysis and Combining Information in Genetics and Genomics

Meta-analysis and Combining Information in Genetics and Genomics

Novel Techniques for Analyzing and Combining Data from Modern Biological StudiesBroadens the Traditional Definition of Meta-Analysis With the diversity of data and meta-data now available there is increased interest in analyzing multiple studies beyond statistical approaches of formal meta-analysis. Covering an extensive range of quantitative information combination methods Meta-analysis and Combining Information in Genetics and Genomics looks at how to analyze multiple studies from a broad perspective. After presenting the basic ideas and tools of meta-analysis the book addresses the combination of similar data types: genotype data from genome-wide linkage scans and data derived from microarray gene expression experiments. The expert contributors show how some data combination problems can arise even within the same basic framework and offer solutions to these problems. They also discuss the combined analysis of different data types giving readers an opportunity to see data combination approaches in action across a wide variety of genome-scale investigations. As heterogeneous data sets become more common biological understanding will be significantly aided by jointly analyzing such data using fundamentally sound statistical methodology. This book provides many novel techniques for analyzing data from modern biological studies that involve multiple data sets either of the same type or multiple data sources.

GBP 69.99
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The Garbage Collection Handbook The Art of Automatic Memory Management

The Garbage Collection Handbook The Art of Automatic Memory Management

Published in 1996 Richard Jones's Garbage Collection was a milestone in the area of automatic memory management. Its widely acclaimed successor The Garbage Collection Handbook: The Art of Automatic Memory Management captured the state of the field in 2012. Modern technology developments have made memory management more challenging interesting and important than ever. This second edition updates the handbook bringing together a wealth of knowledge gathered by automatic memory management researchers and developers over the past sixty years. The authors compare the most important approaches and state-of-the-art techniques in a single accessible framework. The book addresses new challenges to garbage collection made by recent advances in hardware and software. It explores the consequences of these changes for designers and implementers of high performance garbage collectors. Along with simple and traditional algorithms the book covers state-of-the-art parallel incremental concurrent and real-time garbage collection. Algorithms and concepts are often described with pseudocode and illustrations. Features of this edition Provides a complete up-to-date and authoritative sequel to the 1996 and 2012 books Offers thorough coverage of parallel concurrent and real-time garbage collection algorithms Discusses in detail modern high-performance commercial collectors Explains some of the trickier aspects of garbage collection including the interface to the run-time system Over 90 more pages including new chapters on persistence and energy-aware garbage collection Backed by a comprehensive online database of over 3 400 garbage collection-related publications The adoption of garbage collection by almost all modern programming languages makes a thorough understanding of this topic essential for any programmer. This authoritative handbook gives expert insight on how different collectors work as well as the various issues currently facing garbage collectors. Armed with this knowledge programmers can confidently select and configure the many choices of garbage collectors. http://gchandbook. org | The Garbage Collection Handbook The Art of Automatic Memory Management

GBP 59.99
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Handbook of Discrete-Valued Time Series

Handbook of Discrete-Valued Time Series

Model a Wide Range of Count Time Series Handbook of Discrete-Valued Time Series presents state-of-the-art methods for modeling time series of counts and incorporates frequentist and Bayesian approaches for discrete-valued spatio-temporal data and multivariate data. While the book focuses on time series of counts some of the techniques discussed can be applied to other types of discrete-valued time series such as binary-valued or categorical time series. Explore a Balanced Treatment of Frequentist and Bayesian Perspectives Accessible to graduate-level students who have taken an elementary class in statistical time series analysis the book begins with the history and current methods for modeling and analyzing univariate count series. It next discusses diagnostics and applications before proceeding to binary and categorical time series. The book then provides a guide to modern methods for discrete-valued spatio-temporal data illustrating how far modern applications have evolved from their roots. The book ends with a focus on multivariate and long-memory count series. Get Guidance from Masters in the FieldWritten by a cohesive group of distinguished contributors this handbook provides a unified account of the diverse techniques available for observation- and parameter-driven models. It covers likelihood and approximate likelihood methods estimating equations simulation methods and a Bayesian approach for model fitting.

GBP 66.99
1

Automata and Computability A Programmer's Perspective

Automata and Computability A Programmer's Perspective

Automata and Computability is a class-tested textbook which provides a comprehensive and accessible introduction to the theory of automata and computation. The author uses illustrations engaging examples and historical remarks to make the material interesting and relevant for students. It incorporates modern/handy ideas such as derivative-based parsing and a Lambda reducer showing the universality of Lambda calculus. The book also shows how to sculpt automata by making the regular language conversion pipeline available through a simple command interface. A Jupyter notebook will accompany the book to feature code YouTube videos and other supplements to assist instructors and studentsFeatures Uses illustrations engaging examples and historical remarks to make the material accessible Incorporates modern/handy ideas such as derivative-based parsing and a Lambda reducer showing the universality of Lambda calculus Shows how to sculpt automata by making the regular language conversion pipeline available through simple command interface Uses a mini functional programming (FP) notation consisting of lambdas maps filters and set comprehension (supported in Python) to convey math through PL constructs that are succinct and resemble math Provides all concepts are encoded in a compact Functional Programming code that will tesselate with Latex markup and Jupyter widgets in a document that will accompany the books. Students can run code effortlessly. All the code can be accessed here. | Automata and Computability A Programmer's Perspective

GBP 39.99
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Technological Prospects and Social Applications of Society 5.0

Technological Prospects and Social Applications of Society 5.0

This book provides readers to the vision of Society 5. 0 which was originally proposed in the fifth Basic Science and Technology Plan by Japan’s government for a technology-based human-centered society emerging from the fourth industrial revolution (Industry 4. 0). The implementation of AI and other modern techniques in a smart society requires automated data scheduling and analysis using smart applications a smart infrastructure smart systems and a smart network. Features Provides an overview of basic concepts of Society 5. 0 as well as the main pillars that support the implementation of Society 5. 0. Contains the most recent research analysis in the domain of computer vision signal processing and computing sciences for facilitating smart homes buildings transport facilities environmental conditions and cities and the benefits these offer to a nation. Presents the readers with practical approaches of using AI and other algorithms for smart ecosystem to deals with human dynamics the social objects and their relations. Deals with the utilization of AI tools and other modern techniques for smart society as well as the current challenging issues and its solutions for transformation to Society 5. 0. This book is aimed at graduate and post graduate students researchers academicians working in the field of computer science artificial intelligence and machine learning. | Technological Prospects and Social Applications of Society 5. 0

GBP 89.99
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