Introduction to Python Programming And Data Structure By Liang

Python is one of the most popular programming languages, widely used for data analysis and modelling, and is fast becoming the leading choice for scientists and engineers. Unlike other textbooks introducing Python, typically organised by language syntax, this book uses many examples from across Biology, Chemistry, Physics, Earth science, and Engineering to teach and motivate students in science and engineering. The text is organised by the tasks and workflows students undertake day-to-day, helping them see the connections between programming tools and their disciplines. The pace of study is carefully developed for complete beginners, and a spiral pedagogy is used so concepts are introduced across multiple chapters, allowing readers to engage with topics more than once. “Try This!” exercises and online Jupyter notebooks encourage students to test their new knowledge, and further develop their programming skills. Online solutions are available for instructors, alongside discipline-specif

Augment your knowledge of Python with this entertaining learning guide, which features 100 exercises and programming puzzles and solutions. Python Challenges will help prepare you for your next exam or a job interview, and covers numerous practical topics such as strings, data structures, recursion, arrays, and more.Each topic is addressed in its own separate chapter, starting with an introduction to the basics and followed by 10 to 15 exercises of various degrees of difficulty, helping you to improve your programming skills effectively. Detailed sample solutions, including the algorithms used for all tasks, are included to maximize your understanding of each area. Author Michael Inden also describes alternative solutions and analyzes possible pitfalls and typical errors.Three appendices round out the book: the first covers the Python command line interpreter, which is often helpful for trying out the code snippets and examples in the book, followed by an overview of Pytest for unit te

The Hands-On, Example-Rich Introduction to Pandas Data Analysis in Python Today, analysts must manage data characterized by extraordinary variety, velocity, and volume. Using the open source Pandas library, you can use Python to rapidly automate and perform virtually any data analysis task, no matter how large or complex. Pandas can help you ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Pandas for Everyone brings together practical knowledge and insight for solving real problems with Pandas, even if you're new to Python data analysis. Daniel Y. Chen introduces key concepts through simple but practical examples, incrementally building on them to solve more difficult, real-world problems. Chen gives you a jumpstart on using Pandas with a realistic dataset and covers combining datasets, handling missing data, and structuring datasets for easier analysis and visualization. He demonstrates powerful dat

All social and policy researchers need to synthesize data into a visual representation. Producing good visualizations combines creativity and technique. This book teaches the techniques and basics to produce a variety of visualizations, allowing readers to communicate data and analyses in a creative and effective way. Visuals for tables, time series, maps, text, and networks are carefully explained and organized, showing how to choose the right plot for the type of data being analysed and displayed. Examples are drawn from public policy, public safety, education, political tweets, and public health. The presentation proceeds step by step, starting from the basics, in the programming languages R and Python so that readers learn the coding skills while simultaneously becoming familiar with the advantages and disadvantages of each visualization. No prior knowledge of either Python or R is required. Code for all the visualizations are available from the book's website.

All social and policy researchers need to synthesize data into a visual representation. Producing good visualizations combines creativity and technique. This book teaches the techniques and basics to produce a variety of visualizations, allowing readers to communicate data and analyses in a creative and effective way. Visuals for tables, time series, maps, text, and networks are carefully explained and organized, showing how to choose the right plot for the type of data being analysed and displayed. Examples are drawn from public policy, public safety, education, political tweets, and public health. The presentation proceeds step by step, starting from the basics, in the programming languages R and Python so that readers learn the coding skills while simultaneously becoming familiar with the advantages and disadvantages of each visualization. No prior knowledge of either Python or R is required. Code for all the visualizations are available from the book's website.

A textbook that uses a hands-on approach to teach principles of programming languages, with Java as the implementation language.This introductory textbook teaches the principles of programming languages by using an experiential learning style, in which students learn about language features by realizing those features in a pedagogical compiler. Students use Java―the most commonly used programming language in the first two years of the computer science curriculum―as the implementation language throughout. The book also discusses a range of emerging topics in programming languages missing from existing textbooks, including concurrency, Big Data, and event-driven programming. The goal is to prepare students to design, implement, analyze, and understand both domain-specific and general-purpose programming languages. The book first develops basic concepts in languages, including means of computation using primitive values, means of combination such as variable definition and functions, an

Learn How to Better Understand Distributed System Design and Solve Common Problems Enterprises today rely on a range of distributed software handling data storage, messaging, system management, and compute capability. Distributed system designs need to be implemented in some programming language, and there are common problems that these implementations need to solve. These problems have common recurring solutions. A patterns approach is very suitable to describe these implementation aspects. Patterns by nature are generic enough to cover a broad range of products from cloud services like Amazon S3 to message brokers like Apache Kafka to infrastructure frameworks like Kubernetes to databases like MongoDB or Actor frameworks like Akka. At the same time the pattern structure is specific enough to be able to show real code. The beauty of this approach is that even if the code structure is shown in one programming language (Java in this case), the structure applies to many other programming

Functional and concurrent programming paradigms can help experienced object-oriented developers write high-quality software faster: code that's easier to understand, debug, optimize, and evolve. But these approaches have often been surrounded by mystification and misconceptions, leading many developers to avoid them. In Functional and Concurrent Programming, Michel Charpentier clears away the confusion, showing how to use these features safely and well, so you can gain their benefits without their pitfalls. Writing for developers with some object-oriented experience in Java, C++, C#, Python, or elsewhere, Charpentier teaches key concepts through the use of realistic, modern examples: code written in Scala, but relevant to users of any modern object-oriented language. As a hybrid language, Scala can be used effectively to illustrate both object-oriented and functional programming; it offers advanced features for concurrency; and it interoperates with Java, and can use many components of

A new version of the classic and widely used text adapted for the JavaScript programming language.Since the publication of its first edition in 1984 and its second edition in 1996, Structure and Interpretation of Computer Programs (SICP) has influenced computer science curricula around the world. Widely adopted as a textbook, the book has its origins in a popular entry-level computer science course taught by Harold Abelson and Gerald Jay Sussman at MIT. SICP introduces the reader to central ideas of computation by establishing a series of mental models for computation. Earlier editions used the programming language Scheme in their program examples. This new version of the second edition has been adapted for JavaScript. The first three chapters of SICP cover programming concepts that are common to all modern high-level programming languages. Chapters four and five, which used Scheme to formulate language processors for Scheme, required significant revision. Chapter four offers new mat

This commentary covers all topics and critical aspects elicited by the new European General Data Protection Regulation and its interpretation. The commentary focuses on the regulation itself, including cross-references to further provisions (eg the Police and Criminal Justice Data Protection Directive, the E-Privacy-Directive or the former Data Protection Directive 95/46/EC).Article by article the purpose of a provision is classified, its background, function and structure analysed and its content interpreted. The commentary provides an independent view of all topics, presenting both an overview and specific interpretation that provide far-reaching arguments.The editors and authors are outstanding experts in the field of data protection law well known for their practical as well as structured and thorough approach to data protection issues. They offer suitable solutions and sound arguments especially for international companies, legal councils and corporate lawyers as well as data prot

With the advent of the Al era, professionals need to select the right tools to meet new opportunities and challenges! This instructional material focuses on the application of big data analysis, text mining, and machine learning in auditing to assist readers in understanding the latest developments in data analysis and smart audit.JCAATs is a new generation audit software developed by Python, which can be executed in a Windows and MAC operation systems with a multi-language, visual, and easy-to-use interface. Non-IT professionals can easily conduct smart data analysis. Through JCAATs' built-in data fusion technology and OPEN DATA connector, heterogeneous data can be quickly analyzed in real-time and effectively identifying anomalies. The features of this book include:The book is structured to provide a progressive learning experience, with chapters covering different concepts and applications, as well as exercises and practice questions. The official textbook endorsed by ICAEA

Understand the theory and implementation of simulation. This book covers simulation topics from a scenario-driven approach using Python and rich visualizations and tabulations. The book discusses simulation used in the natural and social sciences and with simulations taken from the top algorithms used in the industry today. The authors use an engaging approach that mixes mathematics and programming experiments with beginning-intermediate level Python code to create an immersive learning experience that is cohesive and integrated. After reading this book, you will have an understanding of simulation used in natural sciences, engineering, and social sciences using Python. What You Will LearnUse Python and numerical computation to demonstrate the power of simulationChoose a paradigm to run a simulationDraw statistical insights from numerical experimentsKnow how simulation is used to solve real-world problems Who This Book Is ForEntry-level to mid-level Python developers from various backg

Computational thinking is increasingly gaining importance in modern biology, due to the unprecedented scale at which data is nowadays produced. Bridging the cultural gap between the biological and computational sciences, this book serves as an accessible introduction to computational concepts for students in the life sciences. It focuses on teaching algorithmic and logical thinking, rather than just the use of existing bioinformatics tools or programming. Topics are presented from a biological point of view, to demonstrate how computational approaches can be used to solve problems in biology such as biological image processing, regulatory networks, and sequence analysis. The book contains a range of pedagogical features to aid understanding, including real-world examples, in-text exercises, end-of-chapter problems, colour-coded Python code, and 'code explained' boxes. User-friendly throughout, Computational Thinking for Life Scientists promotes the thinking skills and self-efficacy req

Computational thinking is increasingly gaining importance in modern biology, due to the unprecedented scale at which data is nowadays produced. Bridging the cultural gap between the biological and computational sciences, this book serves as an accessible introduction to computational concepts for students in the life sciences. It focuses on teaching algorithmic and logical thinking, rather than just the use of existing bioinformatics tools or programming. Topics are presented from a biological point of view, to demonstrate how computational approaches can be used to solve problems in biology such as biological image processing, regulatory networks, and sequence analysis. The book contains a range of pedagogical features to aid understanding, including real-world examples, in-text exercises, end-of-chapter problems, colour-coded Python code, and 'code explained' boxes. User-friendly throughout, Computational Thinking for Life Scientists promotes the thinking skills and self-efficacy req

Much of the statistical information currently produced by federal statistical agencies - information about economic, social, and physical well-being that is essential for the functioning of modern society - comes from sample surveys. In recent years, there has been a proliferation of data from other sources, including data collected by government agencies while administering programs, satellite and sensor data, private-sector data such as electronic health records and credit card transaction data, and massive amounts of data available on the internet. How can these data sources be used to enhance the information currently collected on surveys, and to provide new frontiers for producing information and statistics to benefit American society? Toward a 21st Century National Data Infrastructure: Enhancing Survey Programs by Using Multiple Data Sources, the second report in a series funded by the National Science Foundation, discusses how use of multiple data sources can improve the quality

Migrate from pandas and scikit-Learn to PySpark to handle vast amounts of data and achieve faster data processing time. This book will show you how to make this transition by adapting your skills and leveraging the similarities in syntax, functionality, and interoperability between these tools. Distributed Machine Learning with PySpark offers a roadmap to data scientists considering transitioning from small data libraries (pandas/scikit-learn) to big data processing and machine learning with PySpark. You will learn to translate Python code from pandas/scikit-learn to PySpark to preprocess large volumes of data and build, train, test, and evaluate popular machine learning algorithms such as linear and logistic regression, decision trees, random forests, support vector machines, Na鴳e Bayes, and neural networks. After completing this book, you will understand the foundational concepts of data preparation and machine learning and will have the skills necessary to apply these methods using

Computer scientists often need to learn new programming languages quickly. The best way to prepare for this is to understand the foundational principles that underlie even the most complicated industrial languages. This text for an undergraduate programming languages course distills great languages and their design principles down to easy-to-learn 'bridge' languages implemented by interpreters whose key parts are explained in the text. The book goes deep into the roots of both functional and object-oriented programming, and it shows how types and modules, including generics/polymorphism, contribute to effective programming. The book is not just about programming languages; it is also about programming. Through concepts, examples, and more than 300 practice exercises that exploit the interpreter, students learn not only what programming-language features are but also how to do things with them. Substantial implementation projects include Milner's type inference, both copying and mark-an

Hallmark FeaturesIntroduces the fundamental constructs of contemporary programming languages•Critical evaluation of existing and future programming languages gives students the necessary tools for evaluating on their own.•An in-depth discussion of programming language structures, presenting a formal method of describing syntax, and introducing approaches to lexical and syntax analysis prepare students for the study of compiler design.•Coverage of advanced object-oriented topics and languages is integrated throughout.Addresses the most up-to-date information in this field•New - New material on Swift, a contemporary programming language, is now part of several chapters.•New - Section on Delphi now included in Chapter 2.•New - Section on optional types is included in Chapter 6.•New and Updated - Content describing iterations in Python are part of Chapter 8.•Revised - To ensure the material remains relevant to students, sections on outdated languages (specifically Lua and Objective-C) have

Thistitle is a Pearson Global Edition. The editorial team at Pearson has workedclosely with educators around the world to include content which is especiallyrelevant to an international and diverse audience.For courses in computerprogramming.A user-friendly,code-intensive introduction to C programming with case studies introducing applicationsand system programming.C How to Program is a comprehensive introduction toprogramming in C. Like other texts of the Deitels How to Program series,the books modular presentation serves as a detailed, beginner source ofinformation for college students looking to embark on a career in coding, orinstructors and software-development professionals seeking to learn how toprogram with C. The signature Deitel live-code approach presents concepts inthe context of 142 fully working programs rather than incomplete snips of code.This gives students a chance to run each program as they study it and see howtheir learning applies to real-world programming scenari

This text provides deep and comprehensive coverage of the mathematical background for data science, including machine learning, optimal recovery, compressed sensing, optimization, and neural networks. In the past few decades, heuristic methods adopted by big tech companies have complemented existing scientific disciplines to form the new field of Data Science. This text embarks the readers on an engaging itinerary through the theory supporting the field. Altogether, twenty-seven lecture-length chapters with exercises provide all the details necessary for a solid understanding of key topics in data science. While the book covers standard material on machine learning and optimization, it also includes distinctive presentations of topics such as reproducing kernel Hilbert spaces, spectral clustering, optimal recovery, compressed sensing, group testing, and applications of semidefinite programming. Students and data scientists with less mathematical background will appreciate the appendice

An integrated introduction to data visualization, strategic communication, and delivery best practices.Persuading with Data provides an integrated instructional guide to data visualization, strategic communication, and delivery best practices. Most books on data visualization focus on creating good graphs. This is the first book that combines both explanatory visualization and communication strategy, showing how to use visuals to create effective communications that convince an audience to accept and act on the data. In four parts that proceed from macro to micro, the book explains how our brains make sense of graphs; how to design effective graphs and slides that support your ideas; how to organize those ideas into a compelling presentation; and how to deliver and defend data to an audience. Persuading with Data is for anyone who has to explain analytical results to others. It synthesizes a wide range of skills needed by modern data professionals, providing a complete toolkit for cr

Linear regression is the first step, and often the only step, required to fit a simple model to data. Supported by a Glossary and tutorial appendices, this is an ideal introduction to regression analysis. Includes Matlab code.

Learn the fundamental principles of developing structured program logic and be prepared for success with Joyce Farrell�s PROGRAMMING LOGIC AND DESIGN, 10th EDITION. This edition takes a comprehensive and language-independent approach to programming logic with an emphasis on modern conventions. It avoids technical jargon while introducing universal programming concepts and ensuring strong programming style and logical thinking. Chapters contain figures that illustrate the logic described in the text, and there are diverse and project-rich opportunities for you to creatively apply logic to program designs. Flowcharts and pseudocode are employed to appeal to varied learning styles and preferences. Chapters contain learning objectives, notes and short quizzes, summaries, key terms and multiple-choice review. Plus, there are multiple exercises in developing programming logic, maintaining existing programs, debugging programs that contain errors, and developing simple games.

Develop the analytical skills that are in high demand in businesses today with Camm/Cochran/Fry/Ohlmann's best-selling BUSINESS ANALYTICS, 5E. You master the full range of analytics as you strengthen descriptive, predictive and prescriptive analytic skills. Real examples and memorable visuals clearly illustrate data and results. Step-by-step instructions guide you through using Excel, Tableau, R or the Python-based Orange data mining software to perform advanced analytics. Practical, relevant problems at all levels of difficulty let you apply what you've learned. Updates throughout this edition address topics beyond traditional quantitative concepts, such as data wrangling, data visualization and data mining, which are increasingly important in today's business environment. MindTap and WebAssign online learning platforms are also available with an interactive eBook, algorithmic practice problems and Exploring Analytics visualizations to strengthen your understanding of key concepts.

Offering a new perspective, this textbook demystifies the operation of electric machines by providing an integrated understanding of electromagnetic fields, electric circuits, numerical analysis, and computer programming. It presents fundamental concepts in a rigorous manner, emphasising underlying physical modelling assumptions and limitations, and provides detailed explanations of how to implement the finite element method to explore these concepts using Python. It includes explanations of the conversion of concepts into algorithms, and algorithms into code, and examples building in complexity, from simple linear-motion electromagnets to rotating machines. Over 100 theoretical and computational end-of-chapter exercises test understanding, with solutions for instructors and downloadable Python code available online. Ideal for graduates and senior undergraduates studying electric machines, electric machine design and control, and power electronic converters and power systems engineerin

Now in its fourth edition, this comprehensive introduction of fundamental panel data methodologies provides insights on what is most essential in panel literature. A capstone to the forty-year career of a pioneer of panel data analysis, this new edition's primary contribution will be the coverage of advancements in panel data analysis, a statistical method widely used to analyze two or higher-dimensional panel data. The topics discussed in early editions have been reorganized and streamlined to comprehensively introduce panel econometric methodologies useful for identifying causal relationships among variables, supported by interdisciplinary examples and case studies. This book, to be featured in Cambridge's Econometric Society Monographs series, has been the leader in the field since the first edition. It is essential reading for researchers, practitioners and graduate students interested in the analysis of microeconomic behavior.

International edition of Introduction to Management Science: A Modeling and Case Studies Approach with Spreadsheets 7th Edition. Hillier is especially known for his classic, award-winning text, Introduction to Operations Research, co-authored with the late Gerald J. Lieberman, which has been translated into well over a dozen languages and is currently in its 8th edition. The 6th edition won honorable mention for the 1995 Lanchester Prize (best English-language publication of any kind in the field) and Dr. Hillier also was awarded the 2004 INFORMS Expository Writing Award for the 8th edition. His other books include The Evaluation of Risky Interrelated Investments, Queueing Tables and Graphs, Introduction to Stochastic Models in Operations Research, and Introduction to Mathematical Programming. He received his BS in industrial engineering and doctorate specializing in operations research and management science from Stanford University. The winner of many awards in high school and colleg

The dramatic increase in computer performance has been extraordinary, but not for all computations: it has key limits and structure. Software architects, developers, and even data scientists need to understand how exploit the fundamental structure of computer performance to harness it for future applications. Ideal for upper level undergraduates, Computer Architecture for Scientists covers four key pillars of computer performance and imparts a high-level basis for reasoning with and understanding these concepts: Small is fast – how size scaling drives performance; Implicit parallelism – how a sequential program can be executed faster with parallelism; Dynamic locality – skirting physical limits, by arranging data in a smaller space; Parallelism – increasing performance with teams of workers. These principles and models provide approachable high-level insights and quantitative modelling without distracting low-level detail. Finally, the text covers the GPU and machine-learning accelerat

An introduction to computational modeling for cognitive neuroscientists, covering both foundational work and recent developments. Cognitive neuroscientists need sophisticated conceptual tools to make sense of their field’s proliferation of novel theories, methods, and data. Computational modeling is such a tool, enabling researchers to turn theories into precise formulations. This book offers a mathematically gentle and theoretically unified introduction to modeling cognitive processes. Theoretical exercises of varying degrees of difficulty throughout help readers develop their modeling skills. After a general introduction to cognitive modeling and optimization, the book covers models of decision making; supervised learning algorithms, including Hebbian learning, delta rule, and backpropagation; the statistical model analysis methods of model parameter estimation and model evaluation; the three recent cognitive modeling approaches of reinforcement learning, unsupervised learning, and

The essential writings of China’s first iconic modern intellectual, intent on reforming an entire nation, now published for the first time in Penguin ClassicsA Penguin ClassicThe power, anger, and fluency of Liang Qichao’s writings make him one of the towering figures in modern Chinese literature. He saw his great, almost unmanageable task as an attempt to write China into the new era—to provide an ancient country, devastated by civil war and foreign predators, with the intellectual equipment to renew itself.Liang said that he wrote from an “ice-drinker’s studio,” implying that underneath his dispassionate, disabused, and rational tone lay an ardor and passion that only ice could cool. China could recover only through a clear-sighted, informed understanding of its enemies—and by engaging in a thoroughgoing self-critique. Liang did not propose aping the West but taking only what China needed to “renew the people” and create “new citizens.” Then China would be able to expel its invaders,

This new volume addresses the growing interest in and use of big data analytics in many industries and in many research fields around the globe; it is a comprehensive resource on the core concepts of big data analytics and the tools, techniques, and methodologies. The book gives the why and the how of big data analytics in an organized and straightforward manner, using both theoretical and practical approaches.The book's authors have organized the contents in a systematic manner, starting with an introduction and overview of big data analytics and then delving into pre-processing methods, feature selection methods and algorithms, big data streams, and big data classification. Such terms and methods as swarm intelligence, data mining, the bat algorithm and genetic algorithms, big data streams, and many more are discussed. The authors explain how deep learning and machine learning along with other methods and tools are applied in big data analytics. The last section of the book presents

An Introduction to Global Media for the Twenty-First Century provides a thorough introduction to the field of global media today. The book presents the key changes taking place as the global media landscape evolves, and the main theories of the field, that explain these developments.Tracing, first, the formative development of an international and global media landscape throughout the 20th century from the telegraph, television and film export, and transnational television to the Internet, the book then focuses on developments in the 21st century. This includes: the digitization of the global media and communications sector; the popularization of the Internet and digital infrastructure such as the smartphone and platforms; the emergence of global online media and services; the production and distribution of digital media content; and the exploitation of user data. Case studies illustrate key developments throughout the book.The book shows how the field is characterized by a continuity

An Introduction to Global Media for the Twenty-First Century provides a thorough introduction to the field of global media today. The book presents the key changes taking place as the global media landscape evolves, and the main theories of the field, that explain these developments.Tracing, first, the formative development of an international and global media landscape throughout the 20th century from the telegraph, television and film export, and transnational television to the Internet, the book then focuses on developments in the 21st century. This includes: the digitization of the global media and communications sector; the popularization of the Internet and digital infrastructure such as the smartphone and platforms; the emergence of global online media and services; the production and distribution of digital media content; and the exploitation of user data. Case studies illustrate key developments throughout the book.The book shows how the field is characterized by a continuity

Natural phenomena, including human language, are not just series of events but are organized quasi-periodically; sentences have structure, and that structure matters.Howard Lasnik and Juan Uriagereka “were there” when generative grammar was being developed into the Minimalist Program. In this presentation of the universal aspects of human language as a cognitive phenomenon, they rationally reconstruct syntactic structure. In the process, they touch upon structure dependency and its consequences for learnability, nuanced arguments (including global ones) for structure presupposed in standard linguistic analyses, and a formalism to capture long-range correlations. For practitioners, the authors assess whether “all we need is Merge,” while for outsiders, they summarize what needs to be covered when attempting to have structure “emerge.” Reconstructing the essential history of what is at stake when arguing for sentence scaffolding, the authors cover a range of larger issues, from the tradi

This book assesses data protection rules that are applicable to the processing of personal data in a law enforcement context. It offers the first extensive analysis of the LED and Regulation (EU) 2018/1725. It illustrates the challenges arising from the unclear delineation between the different data protection instruments at both national and EU level. Taking a practical approach, it exemplifies situations where the application of data protection instruments could give rise to a lowering of data protection standards where the data protection rules applicable in the law enforcement context are interpreted broadly. The scope of data protection instruments applied by law enforcement authorities impacts processing for purposes of border control, migration management and asylum because there is an unclear delineation between the different data protection instruments.

The second edition of a rigorous and example-driven introduction to topics in economic dynamics that emphasizes techniques for modeling dynamic systems.This text provides an introduction to the modern theory of economic dynamics, with emphasis on mathematical and computational techniques for modeling dynamic systems. Written to be both rigorous and engaging, the book shows how sound understanding of the underlying theory leads to effective algorithms for solving real-world problems. The material makes extensive use of programming examples to illustrate ideas, bringing to life the abstract concepts in the text. Key topics include algorithms and scientific computing, simulation, Markov models, and dynamic programming. Part I introduces fundamentals and part II covers more advanced material. This second edition has been thoroughly updated, drawing on recent research in the field.New for the second edition:“Programming-language agnostic” presentation using pseudocode.New chapter 1 covering

Ideal for entry-level and experienced researchers working in materials science and engineering, this unique book introduces a new subfield of materials science and mechanics of materials: network materials. A comprehensive review of their mechanical behaviours allows readers to understand, design, and enhance the performance of these material systems, across a range of materials including cytoskeletons, connective tissue, and thermoset polymers. By introducing simple models, supported by experimental data, the book provides the necessary fundamental knowledge to assist readers to design and develop their own material systems. By presenting each of these previously disparate material systems within a unified theoretical framework, this book provides a consolidated presentation of the mechanics of networks and their interactions, introducing parameters that define the stochastic structure of the network, and discussing their mechanical behaviour. It is an ideal text for those new to this

Health research around the world relies on access to data, and much of the most valuable, reliable, and comprehensive data collections are held by governments. These collections, which contain data on whole populations, are a powerful tool in the hands of researchers, especially when they are linked and analyzed, and can help to address “wicked problems” in health and emerging global threats such as COVID-19. At the same time, these data collections contain sensitive information that must only be used in ways that respect the values, interests, and rights of individuals and their communities. Sharing Linked Data for Health Research provides a template for allowing research access to government data collections in a regulatory environment designed to build social license while supporting the research enterprise.

Anew title in The QuestKids children's series thatwas launched by In Easy Steps in 2018, designed to make learning fun forchildren.Coding with Python- Create Amazing Graphics introducescoding in Python through a variety of projects. Each one teaches new codingconcepts and results in some amazing graphics.Discover how to mix colours, make patterns, draw 2D and 3Dshapes.Learn how to use loops, variables, random numbers, andfunctions in Python. Packed with challenges, tips, and extensions to keep allbudding coders engaged and eager to keep learning and creating!To create the games in this book, children will need a desktopcomputer or a laptop. The games require a proper keyboard so will not work wellon a tablet or iPad. It is recommended that children should be supervised whenusing the internet, especially when using a new website. Thisis the UK English edition.

An in-depth overview of an emerging field that brings together high-performance computing, big data processing, and deep lLearning. Over the last decade, the exponential explosion of data known as big data has changed the way we understand and harness the power of data. The emerging field of high-performance big data computing, which brings together high-performance computing (HPC), big data processing, and deep learning, aims to meet the challenges posed by large-scale data processing. This book offers an in-depth overview of high-performance big data computing and the associated technical issues, approaches, and solutions. The book covers basic concepts and necessary background knowledge, including data processing frameworks, storage systems, and hardware capabilities; offers a detailed discussion of technical issues in accelerating big data computing in terms of computation, communication, memory and storage, codesign, workload characterization and benchmarking, and system deplo