Programmeringssprog og scriptsprog

4. udgave har fået vejledninger i, hvordan man kommer i gang med de mest udbredte programmeringsværktøjer. Grafikprogrammering er baseret på Swing med nye afsnit om animation, fuldskærmstegning, menuer, genvejstaster, faneblade, dialoger og tabeller (JTable). Eksemplerne er opdateret og forenklet til at følge praksis for Java (TM) 2 Platform Standard Edition 6.0. Introduktion til programmering Bogen starter fra grunden af, men har du ikke programmeret før, bør du være rede til at gøre en indsats, dvs. løbende lave en række små programmer for at øve dig i stoffet. Det forudsættes endvidere, at du har godt kendskab til computere på brugerniveau. En smule kendskab til matematik er også en fordel, men bestemt ikke et krav. Objektorienteret programmering Bogen arbejder grundigt med begreberne omkring objektorienteret programmering (OOP) og giver mange praktiske eksempler på denne måde at programmere på. Den introducerer og anvender løbende relevante dele af UML-notationen, der er meget anvendt i OOP og beslægtede fag som objektorienteret analyse og design. * Objekter * Klasser * Autoboxing * Nedarvning * Polymorfi * Indkapsling * Indre klasser * Interfaces * Analyse og design * Kravslister * Brugssituationer Faciliteterne i Java Programmeringssproget Java har en række faciliteter, der kan lette programmeringen meget. Det overblik, der præsenteres i denne bog, hjælper dig med at udnytte de vigtigste faciliteter samtidig med, at hvert kapitel slutter af med at gå i dybden med en række relevante og avancerede emner. * Grafik * Brugergrænseflader (Swing) * Hændelser * Appletter * Pakker * Tråde * Filhåndtering * Håndtering af undtagelser * Objekt-serialisering * Netværkskommunikation * Databaser * Remote Method Invocation Vælg selv dit værktøj: Borland Jbuilder Eclipse.org Oracle Jdeveloper NetBeans BlueJ

Hvis du gerne vil lære grundlæggende programmering med Microsofts populære programmeringssprog C#, eller har brug for et opslagsværk, har du fat i den helt rigtige bog. Bogen om C# 9.0 er opdelt i følgende kapitler: Introduktion til .NET, Udviklingsmiljøer, Introduktion til C#, Simple variabler, Tekster, Konstanter, Programflow, Metoder, Fejlhåndtering, Arrays, Samlinger, Dine egne typer, Klasser, Hukommelsesteori, Indkapsling, Arv, Polymorfi, Interface, Delegates, Hændelser, LINQ, Avancerede typer, Asynkron programmering.På www.bogenomcsharp.dk kan du desuden finde masser af videoer som understøtter mange af kapitlerne. Bogen kan benyttes som lærebog i C# programmering for private og på uddannelsesinstitutionerne og tager udgangspunkt i både Visual Studio og Visual Studio Code.Bogen er skrevet af Michell Cronberg, som har mange års erfaring med programmering – både som underviser, foredragsholder, konsulent og forfatter. Michell Cronberg har udgivet flere bøger og hæfter om forskellige former for programmering.

Python Crash Course is the world’s bestselling programming book, with over 1,500,000 copies sold to date!Python Crash Course is the world’s best-selling guide to the Python programming language. This fast-paced, thorough introduction will have you writing programs, solving problems, and developing functioning applications in no time.You’ll start by learning basic programming concepts, such as variables, lists, classes, and loops, and practice writing clean code with exercises for each topic. You’ll also learn how to make your programs interactive and test your code safely before adding it to a project. You’ll put your new knowledge into practice by creating a Space Invaders–inspired arcade game, building a set of data visualizations with Python’s handy libraries, and deploying a simple application online.As you work through the book, you’ll learn how to:Use powerful Python libraries and tools, including pytest, Pygame, Matplotlib, Plotly, and DjangoMake increasingly complex 2D games that respond to keypresses and mouse clicksGenerate interactive data visualizations using a variety of datasetsBuild apps that allow users to create accounts and manage their own data, and deploy your apps online Troubleshoot coding errors and solve common programming problems New to this edition: This third edition is completely revised to reflect the latest in Python code. New and updated coverage includes VS Code for text editing, the pathlib module for file handling, pytest for testing your code, as well as the latest features of Matplotlib, Plotly, and Django.If you’ve been thinking about digging into programming, Python Crash Course will provide you with the skills to write real programs fast. Why wait any longer? Start your engines and code!Covers Python 3.x

This book about Visual Basic for Applications (VBA) is different from other books describing VBA for serveral reasons. It is fine-tuned for business applications and in particular business students and it includes business relevant examples. Already in the first chapters the reader is introduced to a variety of different VBA tools, which will enable him or her to write small useful business related programs. In the following chapters the same tools - and more - are presented in a more detailed and rigid way.VBA Programming in Business Economicsis structured as a textbook where each chapter is concluded with a number of exercises which can be used for individual training or as a base for computer-lab teaching. The book's webpage provides case projects that can be used to learn how to combine the material of the book in a larger context. In the situations where examples, exercises, and case projects require knowledge of specific theoretical background, this is provided as short summaries on the books webpage.Besides covering the basic programming, the book also covers programming topics that are more business related: How to use the Excel Solver from within the VBA code, how to perform simulations, and how to construct user forms and make them work with the program. Learning to make useful programs requires more than just writing a number of if- and while statements. Therefore the book also provides a chapter that illustrates how to design and structure a program.In all, this book is a hands-on-guide on VBA for graduate students in Business Economics.

With over 50,000 copies sold, The Rust Programming Language is the quintessential guide to programming in Rust. Thoroughly updated to Rust’s latest version, this edition is considered the language’s official documentation.The Rust Programming Language "covers everything you could want to know about the language."—Stack OverflowRust has been repeatedly voted "Most Loved Language" on the StackOverflow Developer Survey.The Rust Programming Language, 2nd Edition is the official guide to Rust 2021: an open source systems programming language that will help you write faster, more reliable software. Rust provides control of low-level details along with high-level ergonomics, allowing you to improve productivity and eliminate the hassle traditionally associated with low-level languages.Klabnik and Nichols, alumni of the Rust Core Team, share their knowledge to help you get the most out of Rust’s features so that you can create robust and scalable programs. You’ll begin with basics like creating functions, choosing data types, and binding variables, then move on to more advanced concepts, such as:Ownership and borrowing, lifetimes, generics, traits, and trait objects to communicate your program’s constraints to the compilerSmart pointers and multithreading, and how ownership interacts with them to enable fearless concurrencyHow to use Cargo, Rust’s built-in package manager, to build, document your code, and manage dependenciesThe best ways to test, handle errors, refactor, and take advantage of expressive pattern matchingIn addition to the countless code examples, you’ll find three chapters dedicated to building complete projects: a number-guessing game, a Rust implementation of a command line tool, and a multithreaded server.

Beginning-Intermediate user level

Learn how to turn raw data into rich, interactive web visualizations with the powerful combination of Python and JavaScript. With this hands-on guide, author Kyran Dale teaches you how build a basic dataviz toolchain with best-of-breed Python and JavaScript librariesincluding Scrapy, Matplotlib, Pandas, Flask, and D3for crafting engaging, browser-based visualizations.As a working example, throughout the book Dale walks you through transforming Wikipedias table-based list of Nobel Prize winners into an interactive visualization. Youll examine steps along the entire toolchain, from scraping, cleaning, exploring, and delivering data to building the visualization with JavaScripts D3 library. If youre ready to create your own web-based data visualizationsand know either Python or JavaScript this is the book for you.Learn how to manipulate data with PythonUnderstand the commonalities between Python and JavaScriptExtract information from websites by using Pythons web-scraping tools, BeautifulSoup and ScrapyClean and explore data with Pythons Pandas, Matplotlib, and Numpy librariesServe data and create RESTful web APIs with Pythons Flask frameworkCreate engaging, interactive web visualizations with JavaScripts D3 library

This work presents a discourse-aware Text Simplification approach that splits and rephrases complex English sentences within the semantic context in which they occur. Based on a linguistically grounded transformation stage, complex sentences are transformed into shorter utterances with a simple canonical structure that can be easily analyzed by downstream applications. To avoid breaking down the input into a disjointed sequence of statements that is difficult to interpret, the author incorporates the semantic context between the split propositions in the form of hierarchical structures and semantic relationships, thus generating a novel representation of complex assertions that puts a semantic layer on top of the simplified sentences. In a second step, she leverages the semantic hierarchy of minimal propositions to improve the performance of Open IE frameworks. She shows that such systems benefit in two dimensions. First, the canonical structure of the simplified sentences facilitates the extraction of relational tuples, leading to an improved precision and recall of the extracted relations. Second, the semantic hierarchy can be leveraged to enrich the output of existing Open IE approaches with additional meta-information, resulting in a novel lightweight semantic representation for complex text data in the form of normalized and context-preserving relational tuples.

This book constitutes the refereed proceedings of the 12th International Symposium on Foundations of Information and Knowledge Systems, FoIKS 2022, held in Helsinki, Finland, in June 2022. The 13 full papers presented were carefully reviewed and selected from 21 submissions. The papers address various topics such as  information and knowledge systems, including submissions that apply ideas, theories or methods from specific disciplines to information andknowledge systems. Examples of such disciplines are discrete mathematics, logic and algebra, model theory, databases, information theory, complexity theory, algorithmics and computation, statistics and optimization.

In ancient games such as chess or go, the most brilliant players can improve by studying the strategies produced by a machine. Robotic systems practice their own movements. In arcade games, agents capable of learning reach superhuman levels within a few hours. How do these spectacular reinforcement learning algorithms work? With easy-to-understand explanations and clear examples in Java and Greenfoot, you can acquire the principles of reinforcement learning and apply them in your own intelligent agents. Greenfoot (M.Klling, King's College London) and the hamster model (D. Bohles, University of Oldenburg) are simple but also powerful didactic tools that were developed to convey basic programming concepts. The result is an accessible introduction into machine learning that  concentrates on reinforcement learning. Taking the reader through the steps of developing intelligent agents, from the very basics to advanced aspects, touching on a variety of machine learning algorithms along the way, one is allowed to play along, experiment, and add their own ideas and experiments.  

Edited in collaboration with FoLLI, the Association of Logic, Language and Information this book constitutes the refereed proceedings of the 28th Workshop on Logic, Language, Information and Computation, WoLLIC 2022, Iasi, Romania, in September 2022. The 25 full papers presented included with 8 extra abstracts, 5 invited talks and 3 tutorials were fully reviewed and selected from 46 submissions. The conference aims fostering interdisciplinary research in pure and applied logic.

This book constitutes the proceedings of the 41st International Conference on Computer Safety, Reliability and Security, SAFECOMP 2022, which took place in Munich, Germany, in September 2022.The 24 full papers included in this volume were carefully reviewed and selected from 93 submissions. SafeComp has contributed to the progress of the state-of-the-art in dependable application of computers in safety-related and safety-critical systems. SafeComp is an annual event covering the state-of-the-art, experience and new trends in the areas of safety, security and reliability of critical computer applications.

This textbook presents methods and techniques for time series analysis and forecasting and shows how to use Python to implement them and solve data science problems. It covers not only common statistical approaches and time series models, including ARMA, SARIMA, VAR, GARCH and state space and Markov switching models for (non)stationary, multivariate and financial time series, but also modern machine learning procedures and challenges for time series forecasting. Providing an organic combination of the principles of time series analysis and Python programming, it enables the reader to study methods and techniques and practice writing and running Python code at the same time. Its data-driven approach to analyzing and modeling time series data helps new learners to visualize and interpret both the raw data and its computed results. Primarily intended for students of statistics, economics and data science with an undergraduate knowledge of probability and statistics, the book will equally appeal to industry professionals in the fields of artificial intelligence and data science, and anyone interested in using Python to solve time series problems.

This highly accessible textbook teaches programming from first principles. In common with many programming courses, it uses Python as the introductory programming language before going on to use Java as the vehicle for more advanced programming concepts.The first part, which teaches Python, covers fundamental programming concepts, such as data types and control structures and functions. It introduces more complex data types such as lists and dictionaries and also deals with file handling. It introduces object-oriented concepts and ends with a case study bringing together all the topics of the first semester.  The second part uses Java to teach advanced concepts and centres around object-oriented programming, teaching key object-oriented concepts such as inheritance and polymorphism.  The semester again ends with an advanced case study bringing together all the topics of the second semester.Topics and features: Assumes no prior knowledge, and makes the transition from Python to Java a smooth process Features numerous exercises and also an illustrative case study for each language Examines procedural and object-oriented methodologies, as well as design principles Covers such advanced topics as interfaces and lambda expressions, exceptions and Collections Includes a chapter on graphics programming in Python using Tkinter  Introduces the latest Java technology for graphical interfaces, JavaFX Explains design concepts using UML notation Offering a gentle introduction to the field and assuming no prerequisite background, Programming in Two Semesters is the ideal companion to undergraduate modules in software development or programming.  In addition, it will serve as a strong primer for professionals looking to strengthen their knowledge of programming with these languages.

This book introduces the fundamentals of the theory of quantum computing, illustrated with code samples written in Q#, a quantum-specific programming language, and its related Quantum Development Kit. Quantum computing (QC) is a multidisciplinary field that sits at the intersection of quantum physics, quantum information theory, computer science and mathematics, and which may revolutionize the world of computing and software engineering.  The book begins by covering historical aspects of quantum theory and quantum computing, as well as offers a gentle, algebra-based, introduction to quantum mechanics, specifically focusing on concepts essential for the field of quantum programming. Quantum state description, state evolution, quantum measurement and the Bell's theorem are among the topics covered. The readers also get a tour of the features of Q# and familiarize themselves with the QDK.  Next, the core QC topics are discussed, complete with the necessary mathematical formalism. This includes the notions of qubit, quantum gates and quantum circuits. In addition to that, the book provides a detailed treatment of a series of important concepts from quantum information theory, in particular entanglement and the no-cloning theorem, followed by discussion about quantum key distribution and its various protocols. Finally, the canon of most important QC algorithms and algorithmic techniques is covered in-depth - from the Deutsch-Jozsa algorithm, through Grover's search, to Quantum Fourier Transform, quantum phase estimation and Shor's algorithm.   The book is an accessible introduction into the vibrant and fascinating field of quantum computing, offering a blend of academic diligence with pragmatism that is so central to software development world. All of the discussed theoretical aspects of QC are accompanied by runnable code examples, providing the reader with two different angles - mathematical and programmatic - of looking at the same problem space. 

Expert advice on C programming is hard to find. While much help is available for object-oriented programming languages, there's surprisingly little for the C language. With this hands-on guide, beginners and experienced C programmers alike will find guidance about design decisions, including how to apply them bit by bit to running code examples when building large-scale programs.Christopher Preschern, a leading member of the design patterns community, answers questions such as how to structure C programs, cope with error handling, or design flexible interfaces. Whether you're looking for one particular pattern or an overview of design options for a specific topic, this book shows you how to implement hands-on design knowledge specifically for the C programming language.You'll find design patterns for:Error handlingReturning error informationMemory managementReturning data from C functionsData lifetime and ownershipFlexible APIsFlexible iterator interfacesOrganizing files in modular programsEscaping #ifdef Hell

This book will teach you how to build recommender systems with machine learning algorithms using Python. Recommender systems have become an essential part of every internet-based business today.You'll start by learning basic concepts of recommender systems, with an overview of different types of recommender engines and how they function. Next, you will see how to build recommender systems with traditional algorithms such as market basket analysis and content- and knowledge-based recommender systems with NLP. The authors then demonstrate techniques such as collaborative filtering using matrix factorization and hybrid recommender systems that incorporate both content-based and collaborative filtering techniques. This is followed by a tutorial on building machine learning-based recommender systems using clustering and classification algorithms like K-means and random forest. The last chapters cover NLP, deep learning, and graph-based techniques to build a recommender engine. Each chapter includes data preparation, multiple ways to evaluate and optimize the recommender systems, supporting examples, and illustrations.By the end of this book, you will understand and be able to build recommender systems with various tools and techniques with machine learning, deep learning, and graph-based algorithms.What You Will LearnUnderstand and implement different recommender systems techniques with PythonEmploy popular methods like content- and knowledge-based, collaborative filtering, market basket analysis, and matrix factorization Build hybrid recommender systems that incorporate both content-based and collaborative filteringLeverage machine learning, NLP, and deep learning for building recommender systemsWho This Book Is ForData scientists, machine learning engineers, and Python programmers interested in building and implementing recommender systems to solve problems.

Interested in learning how to program with Java? Let's face it, the best way to learn to program is by writing programs. This can be a daunting proposition with the specter of hours of simple command line example programs hanging over your head. Fear not! Now you can learn to program in Java in a fun way by working on video games. With this book, you'll get to work with three Java game projects and have access to the complete game code for each project, including a full Java game engine. After completing Introduction to Java through Game Development, you'll be proficient in Java programming, having worked with the language's fundamental aspects throughout the text, and will be ready to further your Java and game programming expertise with confidence.What You'llMaster the fundamentals of the Java programming languageUse different data structures like arrays, lists, stacks, and queuesUnderstand game programming basics including the main game loopGain experience working with three different game projects via the book's coding challengesWork with the 2D game engine that powers the book's included games and learn to create your own new game projectsUnderstand advanced Java topics like classes, encapsulation, inheritance, and polymorphismWork with exceptions and how to use debugging techniques to trace through codeSharpen your skills with over a dozen coding challenges that test your abilities with a development task on a real game projectWho This Book Is ForThis book requires little to no programming experience to understand and benefit from the text.

This professional guide to Java-based cloud native apps DevOps dives deeper into building and deploying production ready cloud native apps using the increasingly popular open source Eclipse MicroProfile framework, Jakarta EE 10 APIs and the most popular Kubernetes container orchestration tool.After a quick overview of Jakarta EE and MicroProfile, Pro Cloud Native Java EE Apps starts you on your way by walking you through a cloud-native Jakarta EE-based application case study that will be forged piece-by-piece over the course of the book. Next, you'll interject dependencies and data persistence capabilities as microservices to go with the case study app that you are building.  Next, you'll employ the REST API using Jakarta REST APIs and the MicroProfile RESTClient. You'll also explore ways to add resilience to your app, keep count with metrics, check on your app's health, secure your app, and test and complete your production-ready cloud-native app.  Finally, you'll dive into migrating a monolith to become a production ready cloud-native app.  After reading this book, you'll be able to build your own production ready cloud-native Java app using Jakarta EE and MicroProfile. What You Will LearnBuild and deploy a production-ready cloud-native Java app using MicroProfile, Jakarta EE and KubernetesMigrate a monolith app to become a cloud-native appEmploy Jakarta EE APIs such as Persistence, CDI and moreLeverage the MicroProfile frameworkExplore configurations, resilience, metrics, health, security, and more for your cloud-native appsWho This Book Is ForThose software developers and programmers with at least some prior experience using Jakarta EE, MicroProfile. At least some prrior Java experience is expected.

Discover key information buried in the noise of data by learning a variety of anomaly detection techniques and using the Python programming language to build a robust service for anomaly detection against a variety of data types. The book starts with an overview of what anomalies and outliers are and uses the Gestalt school of psychology to explain just why it is that humans are naturally great at detecting anomalies. From there, you will move into technical definitions of anomalies, moving beyond "e;I know it when I see it"e; to defining things in a way that computers can understand.The core of the book involves building a robust, deployable anomaly detection service in Python. You will start with a simple anomaly detection service, which will expand over the course of the book to include a variety of valuable anomaly detection techniques, covering descriptive statistics, clustering, and time series scenarios. Finally, you will compare your anomaly detection service head-to-head with a publicly available cloud offering and see how they perform.The anomaly detection techniques and examples in this book combine psychology, statistics, mathematics, and Python programming in a way that is easily accessible to software developers. They give you an understanding of what anomalies are and why you are naturally a gifted anomaly detector. Then, they help you to translate your human techniques into algorithms that can be used to program computers to automate the process. You'll develop your own anomaly detection service, extend it using a variety of techniques such as including clustering techniques for multivariate analysis and time series techniques for observing data over time, and compare your service head-on against a commercial service.What You Will LearnUnderstand the intuition behind anomaliesConvert your intuition into technical descriptions of anomalous dataDetect anomalies using statistical tools, such as distributions, variance and standard deviation, robust statistics, and interquartile rangeApply state-of-the-art anomaly detection techniques in the realms of clustering and time series analysisWork with common Python packages for outlier detection and time series analysis, such as scikit-learn, PyOD, and tslearnDevelop a project from the ground up which finds anomalies in data, starting with simple arrays of numeric data and expanding to include multivariate inputs and even time series dataWho This Book Is ForFor software developers with at least some familiarity with the Python programming language, and who would like to understand the science and some of the statistics behind anomaly detection techniques. Readers are not required to have any formal knowledge of statistics as the book introduces relevant concepts along the way.

Understand and write programs in Go, a multi-paradigm language with built-in features for concurrent programming. This book enables developers to build software that is simple, reliable, and efficient. It'll also help beginners to start programming Go-based applications.Beginning Go Programming begins by explaining the programming fundamentals of the Go language, including basic syntax, data type and structures, and the use of functions and methods. Next, it covers string formatting, Unicode data handling, and how to use regular expressions in Go. Further, it discusses how to encode and decode JSON formatted data for Go applications, and how to work with HTTP in Go. It concludes by exploring concurrency and covering the most powerful features of Go, as well as tips and tricks related to it. After reading this book and working through its practical examples, you will be ready to begin programming your own Go-based applications.What You Will LearnUnderstand the fundamentals of the Go programming languageMaster the different features of Go and how to implement real-life scenarios using the languageWork with text in Go, such as string formatting and Unicode data handlingWork with HTTP in GoWho This Book Is ForProgrammers and developers looking to learn Go programming language concepts for efficient application building. 

Get a hands-on introduction to Transformer architecture using the Hugging Face library. This book explains how Transformers are changing the AI domain, particularly in the area of natural language processing.This book covers Transformer architecture and its relevance in natural language processing (NLP). It starts with an introduction to NLP and a progression of language models from n-grams to a Transformer-based architecture. Next, it offers some basic Transformers examples using the Google colab engine. Then, it introduces the Hugging Face ecosystem and the different libraries and models provided by it. Moving forward, it explains language models such as Google BERT with some examples before providing a deep dive into Hugging Face API using different language models to address tasks such as sentence classification, sentiment analysis, summarization, and text generation.After completing Introduction to Transformers for NLP, you will understand Transformer concepts and be able to solve problems using the Hugging Face library.What You Will LearnUnderstand language models and their importance in NLP and NLU (Natural Language Understanding)Master Transformer architecture through practical examplesUse the Hugging Face library in Transformer-based language modelsCreate a simple code generator in Python based on Transformer architectureWho This Book Is ForData Scientists and software developers interested in developing their skills in NLP and NLU (Natural Language Understanding)

Learn the Spring Boot 3 micro framework and build your first Java-based cloud-native applications and microservices. Spring Boot is the lightweight, nimbler cousin to the bigger Spring Framework, with plenty of "e;bells and whistles."e; This updated edition includes coverage of Spring Native, which will help you speed up your Spring Boot applications, as well as messaging with Spring Boot, Spring GraphQL, Spring Data JDBC and reactive relational database connectivity (R2DBC) with SQL.This new edition also covers enhancements to actuator endpoints, MongoDB 4.0 support, layered JAR and WAR support, support to build OCI images using Cloud Native Build Packs, changes to the DataSource initialization mechanism, and how bean validation support has moved to a separate spring-boot-validation-starter module. This book will teach you how to work with relational and NoSQL databases for data accessibility using Spring Boot with Spring Data, how to persist data with the Java Persistence APIs (JPA), MyBatis, and much more. You'll learn how to enhance your native cloud or web applications with other APIs such as REST and how to build reactive web applications using Spring Boot with WebFlux. Finally, you'll learn how to test applications using JUnit 5, as well as how to secure and deploy your application or service to cloud providers like Heroku. After reading Beginning Spring Boot 3, you'll have the skills needed to start building your own Spring Boot cloud-native, Java-based applications and microservices with confidence, and to take the next steps in your career. What You Will LearnExplore the Spring Boot 3 micro framework using Spring Native for faster, better performanceBuild cloud-native Java applications and microservices with Spring BootWork with relational and NoSQL databases using Boot with Spring DataCreate reactive web applications using Spring's WebFluxSecure, test, and deploy applications and servicesWho This Book Is ForIT professionals such as cloud architects, infrastructure administrators, and network/cloud operators

In this handy, quick reference book you'll be introduced to several R data science packages, with examples of how to use each of them. All concepts will be covered concisely, with many illustrative examples using the following APIs: readr, dibble, forecasts, lubridate, stringr, tidyr, magnittr, dplyr, purrr, ggplot2, modelr, and more.With R 4 Data Science Quick Reference, you'll have the code, APIs, and insights to write data science-based applications in the R programming language. You'll also be able to carry out data analysis. All source code used in the book is freely available on GitHub..  What You'll LearnImplement applicable R 4 programming language specification featuresImport data with readrWork with categories using forcats, time and dates with lubridate, and strings with stringrFormat data using tidyr and then transform that data using magrittr and dplyrWrite functions with R for data science, data mining, and analytics-based applicationsVisualize data with ggplot2 and fit data to models using modelrWho This Book Is ForProgrammers new to R's data science, data mining, and analytics packages.  Some prior coding experience with R in general is recommended.  

New programmers start here...this book introduces students or aspiring professionals to the world of computer programming using JavaScript and related technologies. This book doesn't just teach the basics of programming, but also all of the tools that new programmers need to get started, including the basics of making web pages and how the Internet works. Programming for Absolute Beginners offers practice problems, activities, and a host of resources to get new programmers started, plus a large glossary of terms introduced in the book and that a new programmer might encounter when learning on their own. No special software is required; this book will help you regardless of what your computer setup is, and source code will be freely available via GitHub.What You Will LearnHow computers workHow computers communicate over networksHow web pages are built with HTML and CSSHow JavaScript worksHow JavaScript interacts with web pagesIntermediate JavaScript topics such as recursion and scopingUsing JavaScript for network communication Who This Book Is ForAnyone wanting to begin computer programming, including students who need to learn the fundamentals and early professionals who want to go back and revisit the basics.

This book introduces the Kotlin programming skills and techniques necessary for building applications. You'll learn how to migrate your Java programming skills to Kotlin, a Java Virtual Machine (JVM) programming language.The book starts with a quick tour of the Kotlin language and gradually walks you through the language in greater detail over the course of succeeding chapters. You'll learn Kotlin fundamentals like generics, functional programming, type system, debugging, and unit testing. Additionally, with the book's freely downloadable online appendices, you'll discover how to use Kotlin for building Spring Boot applications, data persistence, and microservices. What You Will LearnLearn the Kotlin language, its functions, types, collections, generics, classes, and moreDive into higher-order functions, generics, debugging, and unit testingApply the fundamentals of Kotlin to Spring Boot Add Hibernate to your Spring Boot application for persistence and data accessibility Take advantage of functional programming available in KotlinWho This Book Is ForJava developers who are new to Kotlin and want to leverage Kotlin, particularly for building Spring Boot apps.

Learn how to program in modern C, from the basics through the advanced topics required for proficiency. This book is the fastest path to C fluency for anyone experienced in a general-purpose programming language. From start to finish, code examples highlight the idioms and best practices behind efficient, robust programs in a variety of areas.The book opens with a thorough coverage of syntax, built-in data types and operations, and program structure. C has quirks and presents challenges, which are covered in detail. The coverage of advanced features is what sets this book apart from others. Among the advanced topics covered are floating-point representation in the IEEE 754 standard; embedded assembly language in C code for overflow detection; regular expressions, assertions, and internationalization; WebAssembly through C; and software libraries for C and other clients. Memory  efficiency and safety are the two major challenges in C programming, and you'll explore these challenges through a series of C examples. Arrays and structures, which are the means to high-level data representation, are covered in connection with pointers, which provide efficiency. The book again uses code examples in covering networking and wire-level security; concurrency (multiprocessing and multithreading); instruction-level parallelism; and interprocess communication through shared memory and files, pipes, message queues, and signals. Many books introduce C, but few also explain how to use it properly and optimally. Essential C does just that.What You'll LearnAccelerate your path to C mastery with this book for experienced programmersRefresh your approach to program structure and data typesDive into aggregates and pointers using modern C languageRevisit storage classes and scopeDive into concurrency (multiprocessing and multithreading) and instruction-level parallelismFinish with regular expressions, assertions, signals, locales and more Who This Book Is For Professional programmers or software developers who has prior experience with C or in general wanting an accelerated learning guide to modern C programming language.

This book offers comprehensive coverage of the various technologies and techniques used to build technical products. You will learn how technical product development is collaboratively done across multiple technical teams, primarily those in software engineering, data engineering, and AI/ML engineering. You will also be introduced to the technologies these teams use to develop features and products. Many roles in the organization work alongside these technical product development teams and act as liaisons between them, the stakeholders, the customers, and the leadership team. The people in these roles must understand technical aspects ranging from system design to artificial intelligence, and be able to engage in technical discussions with the engineering teams to determine the pros, cons, and risks associated with the development of a technology product or feature.Technical Building Blocks will help you master these technical skills. The book has just the right level of technical details to neither overwhelm with unnecessary technical depth, nor be superficial.From concepts to code snippets, authors Gaurav Sagar and Vitalii Syrovatskyi cover it all to give you an understanding of the engineer's mind and their work. Special emphasis on figures and charts will help you grasp complex ideas more quickly. After reading this book, you'll be able to effectively communicate with engineering teams, provide valuable inputs in the system design review meetings of upcoming features and products, synthesize and simplify technical updates for cross-functional teams and stakeholders, and pass those dreaded technical interviews at your dream companies.What You Will LearnIntrinsic details of the teams and techniques used for product development Concepts of cloud computing and its deployment modelsSystem design fundamentals required to architect features and products   Evolution of data pipelines and data storage solutions to support big dataML and deep learning algorithms to build intelligence into productsSecuring products through identity and access management using cryptographyRole and working of blockchains, smart contracts, NFTs, and dApps in Web3   Who This Book is ForProfessionals in roles who work with software engineering teams and want to build their technical muscle, such as product managers, program managers, business analysts, project managers and product owners. Also useful for those preparing to crack the technical interview for these roles.