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7,875 result(s) for "Processing (programming language)"
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Probabilistic (logic) programming concepts
A multitude of different probabilistic programming languages exists today, all extending a traditional programming language with primitives to support modeling of complex, structured probability distributions. Each of these languages employs its own probabilistic primitives, and comes with a particular syntax, semantics and inference procedure. This makes it hard to understand the underlying programming concepts and appreciate the differences between the different languages. To obtain a better understanding of probabilistic programming, we identify a number of core programming concepts underlying the primitives used by various probabilistic languages, discuss the execution mechanisms that they require and use these to position and survey state-of-the-art probabilistic languages and their implementation. While doing so, we focus on probabilistic extensions of logic programming languages such as Prolog, which have been considered for over 20 years.
Python for the life sciences : a gentle introduction to Python for life scientists
\"Treat yourself to a lively, intuitive, and easy-to-follow introduction to computer programming in Python. The book was written specifically for biologists with little or no prior experience of writing code - with the goal of giving them not only a foundation in Python programming, but also the confidence and inspiration to start using Python in their own research. Virtually all of the examples in the book are drawn from across a wide spectrum of life science research, from simple biochemical calculations and sequence analysis, to modeling the dynamic interactions of genes and proteins in cells, or the drift of genes in an evolving population. Best of all, \"Python for the life sciences\" shows you how to implement all of these projects in Python, one of the most popular programming languages for scientific computing. If you are a life scientist interested in learning Python to jump-start your research, this is the book for you\"--Back cover.
Programming Language Cultures
\"In this book, Brian Lennon demonstrates the power of a philological approach to the history of programming languages and their usage cultures. In chapters focused on specific programming languages such as SNOBOL and JavaScript, as well as on code comments, metasyntactic variables, the very early history of programming, and the concept of DevOps, Lennon emphasizes the histories of programming languages in their individual specificities over their abstract formal or structural characteristics, viewing them as carriers and sometimes shapers of specific cultural histories. The book's philological approach to programming languages presents a natural, sensible, and rigorous way for researchers trained in the humanities to perform research on computing in a way that draws on their own expertise. Combining programming knowledge with a humanistic analysis of the social and historical dimensions of computing, Lennon offers researchers in literar
The SparkFun guide to Processing : create interactive art with code
\"A project-based guide for beginners that teaches how to use the programming language Processing. Covers digital artwork and hardware topics including pixel art, photo editing, video manipulation, 3D design, and using Processing to control an Arduino\"-- Provided by publisher.
Practical Foundations for Programming Languages
Types are the central organizing principle of the theory of programming languages. In this innovative book, Professor Robert Harper offers a fresh perspective on the fundamentals of these languages through the use of type theory. Whereas most textbooks on the subject emphasize taxonomy, Harper instead emphasizes genetics, examining the building blocks from which all programming languages are constructed. Language features are manifestations of type structure. The syntax of a language is governed by the constructs that define its types, and its semantics is determined by the interactions among those constructs. The soundness of a language design – the absence of ill-defined programs – follows naturally. Professor Harper's presentation is simultaneously rigorous and intuitive, relying on elementary mathematics. The framework he outlines scales easily to a rich variety of language concepts and is directly applicable to their implementation. The result is a lucid introduction to programming theory that is both accessible and practical.
Hands-On Concurrency with Rust
Writing safe and correct parallel programs is tough. Reasoning about concurrent memory modification is tough; efficiently exploiting the modern computing environment (with its multi-layered caches and deep execution pipelines) is also tough. Most systems programming languages add a further complication: unsafe memory access. The burden on you,.
Python for finance : mastering data-driven finance
Python has become the programming language of choice for data-driven and AI-first finance. Some of the largest investment banks and hedge funds now use Python and its ecosystem for building core trading and risk management systems. In the second edition of this guide, Yves Hilpisch shows developers and quantitative analysts how to use Python packages and tools for financial data science, algorithmic trading, and computational finance.
Rust Quick Start Guide
Rust is an emerging programming language applicable to areas such as embedded programming, network programming, system programming, and web development. This book will take you from the basics of Rust to the point where your code compiles and does what you intend!.