Products related to Programming:
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R Programming for Actuarial Science
R Programming for Actuarial Science Professional resource providing an introduction to R coding for actuarial and financial mathematics applications, with real-life examples R Programming for Actuarial Science provides a grounding in R programming applied to the mathematical and statistical methods that are of relevance for actuarial work.In R Programming for Actuarial Science, readers will find: Basic theory for each chapter to complement other actuarial textbooks which provide foundational theory in depth. Topics covered include compound interest, statistical inference, asset-liability matching, time series, loss distributions, contingencies, mortality models, and option pricing plus many more typically covered in university courses.More than 400 coding examples and exercises, most with solutions, to enable students to gain a better understanding of underlying mathematical and statistical principles. An overall basic to intermediate level of coverage in respect of numerous actuarial applications, and real-life examples included with every topic. Providing a highly useful combination of practical discussion and basic theory, R Programming for Actuarial Science is an essential reference for BSc/MSc students in actuarial science, trainee actuaries studying privately, and qualified actuaries with little programming experience, along with undergraduate students studying finance, business, and economics.
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Programming Scala : Scalability = Functional Programming + Objects
Get up to speed on Scala--the JVM, JavaScript, and natively compiled language that offers all the benefits of functional programming, a modern object model, and an advanced type system.Packed with code examples, this comprehensive book shows you how to be productive with the language and ecosystem right away.You'll learn why Scala is ideal for building today's highly scalable, data-centric applications, while maximizing developer productivity. While Java remains popular and Kotlin has become popular, Scala hasn't been sitting still.This third edition covers the new features in Scala 3.0 with updates throughout the book.Programming Scala is ideal for beginning to advanced developers who want a complete understanding of Scala's design philosophy and features with a thoroughly practical focus. Program faster with Scala's succinct and flexible syntaxDive into basic and advanced functional programming techniquesBuild killer big data and distributed apps using Scala's functional combinators and tools like Spark and AkkaCreate concise solutions to challenging design problems with the sophisticated type system, mixin composition with traits, pattern matching, and more
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Introduction Functional Programming : Introduction Functional Programming
After the success of the first edition of Introduction to Functional Programming, the authors have thoroughly updated and revised this bestselling title.This book is unusual amongst books on functional programming in that it is primarily directed towards the concepts of functional programming, rather than their realization in a specific programming language.The book clearly expounds the construction of functional programs as a process of mathematical calculation, but the mathematics is restricted to that relevant to the actual construction of programs.
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Data Science Programming All-in-One For Dummies
Your logical, linear guide to the fundamentals of data science programming Data science is exploding—in a good way—with a forecast of 1.7 megabytes of new information created every second for each human being on the planet by 2020 and 11.5 million job openings by 2026.It clearly pays dividends to be in the know. This friendly guide charts a path through the fundamentals of data science and then delves into the actual work: linear regression, logical regression, machine learning, neural networks, recommender engines, and cross-validation of models. Data Science Programming All-In-One For Dummies is a compilation of the key data science, machine learning, and deep learning programming languages: Python and R.It helps you decide which programming languages are best for specific data science needs.It also gives you the guidelines to build your own projects to solve problems in real time. Get grounded: the ideal start for new data professionalsWhat lies ahead: learn about specific areas that data is transforming Be meaningful: find out how to tell your data storySee clearly: pick up the art of visualization Whether you’re a beginning student or already mid-career, get your copy now and add even more meaning to your life—and everyone else’s!
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Programming Challenges : The Programming Contest Training Manual
There are many distinct pleasures associated with computer programming.Craftsmanship has its quiet rewards, the satisfaction that comes from building a useful object and making it work.Excitement arrives with the flash of insight that cracks a previously intractable problem.The spiritual quest for elegance can turn the hacker into an artist.There are pleasures in parsimony, in squeezing the last drop of performance out of clever algorithms and tight coding. The games, puzzles, and challenges of problems from international programming competitions are a great way to experience these pleasures while improving your algorithmic and coding skills.This book contains over 100 problems that have appeared in previous programming contests, along with discussions of the theory and ideas necessary to attack them.Instant onlinegrading for all of these problems is available from two WWW robot judging sites.Combining this book with a judge gives an exciting new way to challenge and improve your programming skills. This book can be used for self-study, for teaching innovative courses in algorithms and programming, and in training for international competition. The problems in this book have been selected from over 1,000 programming problems at the Universidad de Valladolid online judge.The judge has ruled on well over one million submissions from 27,000 registered users around the world to date.We have taken only the best of the best, the most fun, exciting, and interesting problems available.
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Bayesian Data Science with Python : Simulation and Probabilistic Programming
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SQL Programming
Essential Structured Query Language (ANSI SQL-99) six page laminated guide with core commands, statements, syntax and terms for support of beginners who are learning, and experts as a handy quick reference.Author Robin Nixon worked with computers in the 80s and started developing websites in the 90s becoming an expert and writing over 40 programming books and over 500 articles for top computer magazines.With his expertise in the field and writing to his audience in our succinct and organized QuickStudy format, this reference has more quality actionable facts per page than any book or website.Designed for quick access to the facts you need, this inexpensive tool has been a best seller for over 10 years and is an easy add to your programming toolbox.
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Java Programming
Discover the power of Java for developing applications today with the engaging, hands-on approach in Farrell's JAVA PROGRAMMING, 10th edition.Even if you're a first-time programmer, JAVA PROGRAMMING can show you step-by-step how to quickly start developing useful programs, all while mastering the basic principles of structured and object-oriented programming.Up-to-date, reader-friendly explanations and meaningful programming and collaboration exercises emphasize business applications, while useful debugging exercises and contemporary case problems further expand your understanding.Offering anywhere, anytime learning, MindTap equips you with an additional online learning platform, interactive learning tools and auto-graded coding labs for practicing and expanding your skills.
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Similar search terms for Programming:
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What is a programming education?
A programming education is the process of learning how to write, design, and implement computer programs using various programming languages and tools. It involves understanding the fundamental concepts of programming, such as algorithms, data structures, and problem-solving techniques. A programming education also includes learning how to use different programming languages, frameworks, and libraries to develop software applications and systems. Additionally, it involves gaining practical experience through hands-on projects and exercises to apply the knowledge gained in real-world scenarios.
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What is Computer Science Programming 4?
Computer Science Programming 4 is an advanced course that builds on the foundational programming skills learned in earlier courses. It typically covers more complex topics such as data structures, algorithms, and advanced programming techniques. Students may also learn about software development methodologies, debugging, and testing. The course often involves hands-on projects and assignments to apply the concepts learned.
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What is programming in computer science?
Programming in computer science is the process of writing instructions for a computer to execute. It involves using a programming language to create a set of commands that tell the computer how to perform specific tasks or solve problems. Programmers use their knowledge of algorithms, data structures, and logic to write code that can be understood and executed by a computer. Programming is essential for creating software, applications, and systems that power technology and drive innovation in various industries.
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Is programming taught in computer science studies?
Yes, programming is a fundamental part of computer science studies. Students in computer science programs typically learn programming languages such as Python, Java, C++, and others. These languages are used to develop software, algorithms, and applications, and are essential for understanding the principles of computer science. Additionally, programming skills are necessary for solving complex problems and implementing theoretical concepts in practical applications. Therefore, programming is a key component of computer science education.
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What method of programming in computer science?
In computer science, the method of programming refers to the approach or technique used to write and design computer programs. There are various methods of programming, including procedural programming, object-oriented programming, functional programming, and event-driven programming. Each method has its own set of principles and practices for organizing and structuring code to achieve specific goals. The choice of programming method depends on the requirements of the project, the programming language being used, and the preferences of the programmer.
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What is a Java programming task in computer science?
A Java programming task in computer science refers to a task that involves writing code in the Java programming language to solve a specific problem or implement a particular functionality. This could include tasks such as creating algorithms, designing data structures, building user interfaces, or developing applications. Java is a widely-used programming language in computer science due to its platform independence, object-oriented approach, and extensive libraries, making it a common choice for various programming tasks.
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What is the topic of computer science Python programming?
The topic of computer science Python programming is the use of the Python programming language to develop software and applications. This includes learning the syntax and structure of Python, understanding how to write and execute code, and applying Python to solve various computational problems. Additionally, the topic covers the use of Python for data analysis, web development, artificial intelligence, and other areas of computer science. Overall, the focus is on using Python as a tool for programming and problem-solving within the field of computer science.
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Do you learn programming in a computer science degree?
Yes, programming is a fundamental aspect of a computer science degree. Students typically learn various programming languages such as Java, C++, Python, and others. Programming assignments and projects are commonly used to help students develop problem-solving skills and understand key concepts in computer science. Additionally, courses in data structures, algorithms, and software development often involve significant programming components.
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