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Introduction to Financial Mathematics With Computer Applications

Introduction to Financial Mathematics With Computer Applications

This book’s primary objective is to educate aspiring finance professionals about mathematics and computation in the context of financial derivatives. The authors offer a balance of traditional coverage and technology to fill the void between highly mathematical books and broad finance books. The focus of this book is twofold: To partner mathematics with corresponding intuition rather than diving so deeply into the mathematics that the material is inaccessible to many readers. To build reader intuition understanding and confidence through three types of computer applications that help the reader understand the mathematics of the models. Unlike many books on financial derivatives requiring stochastic calculus this book presents the fundamental theories based on only undergraduate probability knowledge. A key feature of this book is its focus on applying models in three programming languages –R Mathematica and EXCEL. Each of the three approaches offers unique advantages. The computer applications are carefully introduced and require little prior programming background. The financial derivative models that are included in this book are virtually identical to those covered in the top financial professional certificate programs in finance. The overlap of financial models between these programs and this book is broad and deep. | Introduction to Financial Mathematics With Computer Applications

GBP 89.99
1

Metabolomics Practical Guide to Design and Analysis

Metabolomics Practical Guide to Design and Analysis

Metabolomics is the scientific study of the chemical processes in a living system environment and nutrition. It is a relatively new omics science but the potential applications are wide including medicine personalized medicine and intervention studies food and nutrition plants agriculture and environmental science. The topics presented and discussed in this book are based on the European Molecular Biology Organization (EMBO) practical courses in metabolomics bioinformatics taught to those working in the field from masters to postgraduate students PhDs postdoctoral and early PIs. The book covers the basics and fundamentals of data acquisition and analytical technologies but the primary focus is data handling and data analysis. The mentioning and usage of a particular data analysis tool has been avoided; rather the focus is on the concepts and principles of data processing and analysis. The material has been class-tested and includes lots of examples computing and exercises. Key Features:Provides an overview of qualitative /quantitative methods in metabolomicsOffers an introduction to the key concepts of metabolomics including experimental design and technologyCovers data handling processing analysis data standards and sharingContains lots of examples to illustrate the topicsIncludes contributions from some of the leading researchers in the field of metabolomics with extensive teaching experiences | Metabolomics Practical Guide to Design and Analysis

GBP 44.99
1

Cybersecurity A Practical Engineering Approach

Cybersecurity A Practical Engineering Approach

Cybersecurity: A Practical Engineering Approach introduces the implementation of a secure cyber architecture beginning with the identification of security risks. It then builds solutions to mitigate risks by considering the technological justification of the solutions as well as their efficiency. The process follows an engineering process model. Each module builds on a subset of the risks discussing the knowledge necessary to approach a solution followed by the security control architecture design and the implementation. The modular approach allows students to focus on more manageable problems making the learning process simpler and more attractive. | Cybersecurity A Practical Engineering Approach

GBP 66.99
1

Multilevel Modeling Using Mplus

Multilevel Modeling Using Mplus

This book is designed primarily for upper level undergraduate and graduate level students taking a course in multilevel modelling and/or statistical modelling with a large multilevel modelling component. The focus is on presenting the theory and practice of major multilevel modelling techniques in a variety of contexts using Mplus as the software tool and demonstrating the various functions available for these analyses in Mplus which is widely used by researchers in various fields including most of the social sciences. In particular Mplus offers users a wide array of tools for latent variable modelling including for multilevel data. | Multilevel Modeling Using Mplus

GBP 180.00
1

Real-World Evidence in a Patient-Centric Digital Era

Real-World Evidence in a Patient-Centric Digital Era

Real-world evidence is defined as evidence generated from real-world data outside randomized controlled trials. As scientific discoveries and methodologies continue to advance real-world data and their companion technologies offer powerful new tools for evidence generation. Real-World Evidence in a Patient-Centric Digital Era provides perspectives examples and insights on the innovative application of real-world evidence to meet patient needs and improve healthcare with a focus on the pharmaceutical industry. This book presents an overview of key analytical issues and best practices. Special attention is paid to the development methodologies and other salient features of the statistical and data science techniques that are customarily used to generate real-world evidence. It provides a review of key topics and emerging trends in cutting-edge data science and health innovation. Features: Provides an overview of statistical and analytic methodologies in real-world evidence to generate insights on healthcare with a special focus on the pharmaceutical industry Examines timely topics of high relevance to industry such as bioethical considerations regulatory standards and compliance requirements Highlights emerging and current trends and provides guidelines for best practices Illustrates methods through examples and use-case studies to demonstrate impact Provides guidance on software choices and digital applications for successful analytics Real-World Evidence in a Patient-Centric Digital Era will be a vital reference for medical researchers health technology innovators data scientists epidemiologists population health analysts health economists outcomes researchers policymakers and analysts in the healthcare industry.

GBP 99.99
1

Crime Mapping and Spatial Data Analysis using R

Crime Mapping and Spatial Data Analysis using R

Crime mapping and analysis sit at the intersection of geocomputation data visualisation and cartography spatial statistics environmental criminology and crime analysis. This book brings together relevant knowledge from these fields into a practical hands-on guide providing a useful introduction and reference material for topics in crime mapping the geography of crime environmental criminology and crime analysis. It can be used by students practitioners and academics alike whether to develop a university course to support further training and development or to hone skills in self-teaching R and crime mapping and spatial data analysis. It is not an advanced statistics textbook but rather an applied guide and later useful reference books intended to be read and for readers to practice the learnings from each chapter in sequence. In the first part of this volume we introduce key concepts for geographic analysis and representation and provide the reader with the foundations needed to visualise spatial crime data. We then introduce a series of tools to study spatial homogeneity and dependence. A key focus in this section is how to visualise and detect local clusters of crime and repeat victimisation. The final chapters introduce the use of basic spatial models which account for the distribution of crime across space. In terms of spatial data analysis the focus of the book is on spatial point pattern analysis and lattice or area data analysis.   | Crime Mapping and Spatial Data Analysis using R

GBP 74.99
1

Big Data in Multimodal Medical Imaging

Big Data in Multimodal Medical Imaging

There is an urgent need to develop and integrate new statistical mathematical visualization and computational models with the ability to analyze Big Data in order to retrieve useful information to aid clinicians in accurately diagnosing and treating patients. The main focus of this book is to review and summarize state-of-the-art big data and deep learning approaches to analyze and integrate multiple data types for the creation of a decision matrix to aid clinicians in the early diagnosis and identification of high risk patients for human diseases and disorders. Leading researchers will contribute original research book chapters analyzing efforts to solve these important problems. | Big Data in Multimodal Medical Imaging

GBP 44.99
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Geocomputation with R

Geocomputation with R

Geocomputation with R is for people who want to analyze visualize and model geographic data with open source software. It is based on R a statistical programming language that has powerful data processing visualization and geospatial capabilities. The book equips you with the knowledge and skills to tackle a wide range of issues manifested in geographic data including those with scientific societal and environmental implications. This book will interest people from many backgrounds especially Geographic Information Systems (GIS) users interested in applying their domain-specific knowledge in a powerful open source language for data science and R users interested in extending their skills to handle spatial data. The book is divided into three parts: (I) Foundations aimed at getting you up-to-speed with geographic data in R (II) extensions which covers advanced techniques and (III) applications to real-world problems. The chapters cover progressively more advanced topics with early chapters providing strong foundations on which the later chapters build. Part I describes the nature of spatial datasets in R and methods for manipulating them. It also covers geographic data import/export and transforming coordinate reference systems. Part II represents methods that build on these foundations. It covers advanced map making (including web mapping) bridges to GIS sharing reproducible code and how to do cross-validation in the presence of spatial autocorrelation. Part III applies the knowledge gained to tackle real-world problems including representing and modeling transport systems finding optimal locations for stores or services and ecological modeling. Exercises at the end of each chapter give you the skills needed to tackle a range of geospatial problems. Solutions for each chapter and supplementary materials providing extended examples are available at https://geocompr. github. io/geocompkg/articles/. Dr. Robin Lovelace is a University Academic Fellow at the University of Leeds where he has taught R for geographic research over many years with a focus on transport systems. Dr. Jakub Nowosad is an Assistant Professor in the Department of Geoinformation at the Adam Mickiewicz University in Poznan where his focus is on the analysis of large datasets to understand environmental processes. Dr. Jannes Muenchow is a Postdoctoral Researcher in the GIScience Department at the University of Jena where he develops and teaches a range of geographic methods with a focus on ecological modeling statistical geocomputing and predictive mapping. All three are active developers and work on a number of R packages including stplanr sabre and RQGIS.

GBP 44.99
1

Evaluating What Works An Intuitive Guide to Intervention Research for Practitioners

Evaluating What Works An Intuitive Guide to Intervention Research for Practitioners

Those who work in allied health professions and education aim to make people’s lives better. Often however it is hard to know how effective this work has been: would change have occurred if there was no intervention? Is it possible we are doing more harm than good? To answer these questions and develop a body of knowledge about what works we need to evaluate interventions. Objective intervention research is vital to improve outcomes but this is a complex area where it is all too easy to misinterpret evidence. This book uses practical examples to increase awareness of the numerous sources of bias that can lead to mistaken conclusions when evaluating interventions. The focus is on quantitative research methods and exploration of the reasons why those both receiving and implementing intervention behave in the ways they do. Evaluating What Works: Intuitive Guide to Intervention Research for Practitioners illustrates how different research designs can overcome these issues and points the reader to sources with more in-depth information. This book is intended for those with little or no background in statistics to give them the confidence to approach statistics in published literature with a more critical eye recognise when more specialist advice is needed and give them the ability to communicate more effectively with statisticians. Key Features: Strong focus on quantitative research methods Complements more technical introductions to statistics Provides a good explanation of how quantitative studies are designed and what biases and pitfalls they can involve | Evaluating What Works An Intuitive Guide to Intervention Research for Practitioners

GBP 44.99
1

Discovering Evolution Equations with Applications Volume 2-Stochastic Equations

Discovering Evolution Equations with Applications Volume 2-Stochastic Equations

Most existing books on evolution equations tend either to cover a particular class of equations in too much depth for beginners or focus on a very specific research direction. Thus the field can be daunting for newcomers to the field who need access to preliminary material and behind-the-scenes detail. Taking an applications-oriented conversational approach Discovering Evolution Equations with Applications: Volume 2-Stochastic Equations provides an introductory understanding of stochastic evolution equations. The text begins with hands-on introductions to the essentials of real and stochastic analysis. It then develops the theory for homogenous one-dimensional stochastic ordinary differential equations (ODEs) and extends the theory to systems of homogenous linear stochastic ODEs. The next several chapters focus on abstract homogenous linear nonhomogenous linear and semi-linear stochastic evolution equations. The author also addresses the case in which the forcing term is a functional before explaining Sobolev-type stochastic evolution equations. The last chapter discusses several topics of active research. Each chapter starts with examples of various models. The author points out the similarities of the models develops the theory involved and then revisits the examples to reinforce the theoretical ideas in a concrete setting. He incorporates a substantial collection of questions and exercises throughout the text and provides two layers of hints for selected exercises at the end of each chapter. Suitable for readers unfamiliar with analysis even at the undergraduate level this book offers an engaging and accessible account of core theoretical results of stochastic evolution equations in a way that gradually builds readers’ intuition. | Discovering Evolution Equations with Applications Volume 2-Stochastic Equations

GBP 69.99
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A Course on Statistics for Finance

A Course on Statistics for Finance

Taking a data-driven approach A Course on Statistics for Finance presents statistical methods for financial investment analysis. The author introduces regression analysis time series analysis and multivariate analysis step by step using models and methods from finance. The book begins with a review of basic statistics including descriptive statistics kinds of variables and types of data sets. It then discusses regression analysis in general terms and in terms of financial investment models such as the capital asset pricing model and the Fama/French model. It also describes mean-variance portfolio analysis and concludes with a focus on time series analysis. Providing the connection between elementary statistics courses and quantitative finance courses this text helps both existing and future quants improve their data analysis skills and better understand the modeling process.

GBP 44.99
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Computational Statistics Handbook with MATLAB

Computational Statistics Handbook with MATLAB

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

GBP 44.99
1

The History of the International Biometric Society

The History of the International Biometric Society

The International Biometric Society (IBS) was formed at the First International Biometric Conference at Woods Hole on September 6 1947. The History of the International Biometric Society presents a deep dive into the voluminous archival records with primary focus on IBS’s first fifty years. It contains numerous photos and extracts from the archival materials and features many photos of important leaders who served IBS across the decades. Features: Describes events leading up to and at Woods Hole on September 6 1947 that led to the formation of IBS Outlines key markers that shaped IBS after the 1947 formation through to the modern day Describes the regional and national group structure and the formation of regions and national groups Describes events surrounding the key scientific journal of IBS Biometrics including the transfer of ownership to IBS content editors policies management and importance Describes the other key IBS publications – Biometric Bulletin Journal of Agricultural Biological and Environmental Statistics and regional publications Provides details of International Biometric Conferences and key early symposia Describes IBS constitution and by-laws processes and the evolution of business arrangements Provides a record of international officers including regional presidents national group secretaries journal editors and the locations of meetings Includes a gallery of international Presidents and a gallery of Secretaries and Treasurers The History of the International Biometric Society will appeal to anyone interested in the activities of our statistical and biometrical forebearers. The focus is on issues and events that engaged the attention of the officers of IBS. Some of these records are riveting some entertaining some intriguing and some colorful. Some of the issues covered were difficult to handle but even these often resulted in changes that benefited IBS.

GBP 44.99
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Survival Analysis with Interval-Censored Data A Practical Approach with Examples in R SAS and BUGS

Survival Analysis with Interval-Censored Data A Practical Approach with Examples in R SAS and BUGS

Survival Analysis with Interval-Censored Data: A Practical Approach with Examples in R SAS and BUGS provides the reader with a practical introduction into the analysis of interval-censored survival times. Although many theoretical developments have appeared in the last fifty years interval censoring is often ignored in practice. Many are unaware of the impact of inappropriately dealing with interval censoring. In addition the necessary software is at times difficult to trace. This book fills in the gap between theory and practice. Features:-Provides an overview of frequentist as well as Bayesian methods. Include a focus on practical aspects and applications. Extensively illustrates the methods with examples using R SAS and BUGS. Full programs are available on a supplementary website. The authors:Kris Bogaerts is project manager at I-BioStat KU Leuven. He received his PhD in science (statistics) at KU Leuven on the analysis of interval-censored data. He has gained expertise in a great variety of statistical topics with a focus on the design and analysis of clinical trials. Arnošt Komárek is associate professor of statistics at Charles University Prague. His subject area of expertise covers mainly survival analysis with the emphasis on interval-censored data and classification based on longitudinal data. He is past chair of the Statistical Modelling Society and editor of Statistical Modelling: An International Journal. Emmanuel Lesaffre is professor of biostatistics at I-BioStat KU Leuven. His research interests include Bayesian methods longitudinal data analysis statistical modelling analysis of dental data interval-censored data misclassification issues and clinical trials. He is the founding chair of the Statistical Modelling Society past-president of the International Society for Clinical Biostatistics and fellow of ISI and ASA. | Survival Analysis with Interval-Censored Data A Practical Approach with Examples in R SAS and BUGS

GBP 44.99
1

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

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

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

GBP 89.99
1

Monomial Algebras

Monomial Algebras

Monomial Algebras Second Edition presents algebraic combinatorial and computational methods for studying monomial algebras and their ideals including Stanley–Reisner rings monomial subrings Ehrhart rings and blowup algebras. It emphasizes square-free monomials and the corresponding graphs clutters or hypergraphs. New to the Second Edition Four new chapters that focus on the algebraic properties of blowup algebras in combinatorial optimization problems of clutters and hypergraphs Two new chapters that explore the algebraic and combinatorial properties of the edge ideal of clutters and hypergraphs Full revisions of existing chapters to provide an up-to-date account of the subject Bringing together several areas of pure and applied mathematics this book shows how monomial algebras are related to polyhedral geometry combinatorial optimization and combinatorics of hypergraphs. It directly links the algebraic properties of monomial algebras to combinatorial structures (such as simplicial complexes posets digraphs graphs and clutters) and linear optimization problems.

GBP 74.99
1

Healthcare 4.0 Health Informatics and Precision Data Management

Healthcare 4.0 Health Informatics and Precision Data Management

The main aim of Healthcare 4. 0: Health Informatics and Precision Data Management is to improve the services given by the healthcare industry and to bring meaningful patient outcomes by applying the data information and knowledge in the healthcare domain. Features: Improves the quality of health data of a patient Presents a wide range of opportunities and renewed possibilities for healthcare systems Gives a way for carefully and meticulously tracking the provenance of medical records Accelerates the process of disease-oriented data and medical data arbitration Brings meaningful patient health outcomes Eradicates delayed clinical communications Helps the research intellectuals to step down further toward the disease and clinical data storage Creates more patient-centered services The precise focus of this handbook is on the potential applications and use of data informatics in healthcare including clinical trials tailored ailment data patient and ailment record characterization and health records management. | Healthcare 4. 0 Health Informatics and Precision Data Management

GBP 140.00
1

Piece-wise and Max-Type Difference Equations Periodic and Eventually Periodic Solutions

Piece-wise and Max-Type Difference Equations Periodic and Eventually Periodic Solutions

Piece-wise and Max-Type Difference Equations: Periodic and Eventually Periodic Solutions is intended for lower-level undergraduate students studying discrete mathematics. The book focuses on sequences as recursive relations and then transitions to periodic recursive patterns and eventually periodic recursive patterns. In addition to this it will also focus on determining the patterns of periodic and eventually periodic solutions inductively. The aim of the author throughout this book is to get students to understand the significance of pattern recognition as a mathematical tool. Key Features Can provide possible topics for undergraduate research and for bachelor’s thesis Provides supplementary practice problems and some open-ended research problems at the end of each chapter Focusses on determining the patterns of periodic and eventually periodic solutions inductively Enhances students’ algebra skills before moving forward to upper level courses Familiarize students with the topics before they start undergraduate research by providing applications. | Piece-wise and Max-Type Difference Equations Periodic and Eventually Periodic Solutions

GBP 44.99
1

Geographic Data Science with R Visualizing and Analyzing Environmental Change

Geographic Data Science with R Visualizing and Analyzing Environmental Change

The burgeoning field of data science has provided a wealth of techniques for analysing large and complex geospatial datasets including descriptive explanatory and predictive analytics. However applying these methods is just one part of the overall process of geographic data science. Other critical steps include screening for suspect data values handling missing data harmonizing data from multiple sources summarizing the data and visualizing data and analysis results. Although there are many books available on statistical and machine learning methods few encompass the broader topic of scientific workflows for geospatial data processing and analysis. The purpose of Geographic Data Science with R is to fill this gap by providing a series of tutorials aimed at teaching good practices for using geospatial data to address problems in environmental geography. It is based on the R language and environment which currently provides the best option for working with diverse spatial and non-spatial data in a single platform. Fundamental techniques for processing and visualizing tabular vector and raster data are introduced through a series of practical examples followed by case studies that combine multiple types of data to address more complex problems. The book will have a broad audience. Both students and professionals can use it as a workbook to learn high-level techniques for geospatial data processing and analysis with R. It is also suitable as a textbook. Although not intended to provide a comprehensive introduction to R it is designed to be accessible to readers who have at least some knowledge of coding but little to no experience with R. Key Features: Focus on developing practical workflows for processing and integrating multiple sources of geospatial data in R Example-based approach that teaches R programming and data science concepts through real-world applications related to climate land cover and land use and natural hazards. Consistent use of tidyverse packages for tabular data manipulation and visualization. Strong focus on analysing continuous and categorical raster datasets using the new terra package Organized so that each chapter builds on the topics and techniques covered in the preceding chapters Can be used for self-study or as the textbook for a geospatial science course. | Geographic Data Science with R Visualizing and Analyzing Environmental Change

GBP 74.99
1

Basic Matrix Algebra with Algorithms and Applications

Basic Matrix Algebra with Algorithms and Applications

Clear prose tight organization and a wealth of examples and computational techniques make Basic Matrix Algebra with Algorithms and Applications an outstanding introduction to linear algebra. The author designed this treatment specifically for freshman majors in mathematical subjects and upper-level students in natural resources the social sciences business or any discipline that eventually requires an understanding of linear models. With extreme pedagogical clarity that avoids abstraction wherever possible the author emphasizes minimal polynomials and their computation using a Krylov algorithm. The presentation is highly visual and relies heavily on work with a graphing calculator to allow readers to focus on concepts and techniques rather than on tedious arithmetic. Supporting materials including test preparation Maple worksheets are available for download from the Internet. This unassuming but insightful and remarkably original treatment is organized into bite-sized clearly stated objectives. It goes well beyond the LACSG recommendations for a first course while still implementing their philosophy and core material. Classroom tested with great success it prepares readers well for the more advanced studies their fields ultimately will require.

GBP 175.00
1

Human-Robot Interaction Safety Standardization and Benchmarking

Human-Robot Interaction Safety Standardization and Benchmarking

Human-Robot Interaction: Safety Standardization and Benchmarking provides a comprehensive introduction to the new scenarios emerging where humans and robots interact in various environments and applications on a daily basis. The focus is on the current status and foreseeable implications of robot safety approaching these issues from the standardization and benchmarking perspectives. Featuring contributions from leading experts the book presents state-of-the-art research and includes real-world applications and use cases. It explores the key leading sectors—robotics service robotics and medical robotics—and elaborates on the safety approaches that are being developed for effective human-robot interaction including physical robot-human contacts collaboration in task execution workspace sharing human-aware motion planning and exploring the landscape of relevant standards and guidelines. FeaturesPresenting a comprehensive introduction to human-robot interaction in a number of domains including industrial robotics medical robotics and service roboticsFocusing on robot safety standards and benchmarkingProviding insight into current developments in international standardsFeaturing contributions from leading experts actively pursuing new robot development | Human-Robot Interaction Safety Standardization and Benchmarking

GBP 44.99
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Numerical Methods for Unsteady Compressible Flow Problems

Numerical Methods for Unsteady Compressible Flow Problems

Numerical Methods for Unsteady Compressible Flow Problems is written to give both mathematicians and engineers an overview of the state of the art in the field as well as of new developments. The focus is on methods for the compressible Navier-Stokes equations the solutions of which can exhibit shocks boundary layers and turbulence. The idea of the text is to explain the important ideas to the reader while giving enough detail and pointers to literature to facilitate implementation of methods and application of concepts. The book covers high order methods in space such as Discontinuous Galerkin methods and high order methods in time in particular implicit ones. A large part of the text is reserved to discuss iterative methods for the arising large nonlinear and linear equation systems. Ample space is given to both state-of-the-art multigrid and preconditioned Newton-Krylov schemes. Features Applications to aerospace high-speed vehicles heat transfer and more besides Suitable as a textbook for graduate-level courses in CFD or as a reference for practitioners in the field

GBP 44.99
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Machine Learning in Signal Processing Applications Challenges and the Road Ahead

Machine Learning in Signal Processing Applications Challenges and the Road Ahead

Machine Learning in Signal Processing: Applications Challenges and the Road Ahead offers a comprehensive approach toward research orientation for familiarizing signal processing (SP) concepts to machine learning (ML). ML as the driving force of the wave of artificial intelligence (AI) provides powerful solutions to many real-world technical and scientific challenges. This book will present the most recent and exciting advances in signal processing for ML. The focus is on understanding the contributions of signal processing and ML and its aim to solve some of the biggest challenges in AI and ML. FEATURES Focuses on addressing the missing connection between signal processing and ML Provides a one-stop guide reference for readers Oriented toward material and flow with regards to general introduction and technical aspects Comprehensively elaborates on the material with examples and diagrams This book is a complete resource designed exclusively for advanced undergraduate students post-graduate students research scholars faculties and academicians of computer science and engineering computer science and applications and electronics and telecommunication engineering. | Machine Learning in Signal Processing Applications Challenges and the Road Ahead

GBP 150.00
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The Essentials of Data Science: Knowledge Discovery Using R

The Essentials of Data Science: Knowledge Discovery Using R

The Essentials of Data Science: Knowledge Discovery Using R presents the concepts of data science through a hands-on approach using free and open source software. It systematically drives an accessible journey through data analysis and machine learning to discover and share knowledge from data. Building on over thirty years’ experience in teaching and practising data science the author encourages a programming-by-example approach to ensure students and practitioners attune to the practise of data science while building their data skills. Proven frameworks are provided as reusable templates. Real world case studies then provide insight for the data scientist to swiftly adapt the templates to new tasks and datasets. The book begins by introducing data science. It then reviews R’s capabilities for analysing data by writing computer programs. These programs are developed and explained step by step. From analysing and visualising data the framework moves on to tried and tested machine learning techniques for predictive modelling and knowledge discovery. Literate programming and a consistent style are a focus throughout the book.

GBP 145.00
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An Introduction to Metric Spaces

An Introduction to Metric Spaces

This book serves as a textbook for an introductory course in metric spaces for undergraduate or graduate students. The goal is to present the basics of metric spaces in a natural and intuitive way and encourage students to think geometrically while actively participating in the learning of this subject. In this book the authors illustrated the strategy of the proofs of various theorems that motivate readers to complete them on their own. Bits of pertinent history are infused in the text including brief biographies of some of the central players in the development of metric spaces. The textbook is divided into seven chapters that contain the main materials on metric spaces; namely introductory concepts completeness compactness connectedness continuous functions and metric fixed point theorems with applications. Some of the noteworthy features of this book include · Diagrammatic illustrations that encourage readers to think geometrically · Focus on systematic strategy to generate ideas for the proofs of theorems · A wealth of remarks observations along with a variety of exercises · Historical notes and brief biographies appearing throughout the text | An Introduction to Metric Spaces

GBP 32.99
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