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Nichols C: The Rust Programming
Language, 3rd Edition

The Rust Programming Language, 3rd Edition

Foreword Preface Acknowledgments Introduction Chapter 1: Getting Started Chapter 2: Programming a Guessing Game Chapter 3: Common Programming Concepts Chapter 4: Understanding Ownership Chapter 5: Using Structs to Structure Related Data Chapter 6: Enums and Pattern Matching Chapter 7: Managing Growing Projects with Packages, Crates, and Modules Chapter 8: Common Collections Chapter 9: Error Handling Chapter 10: Generic Types, Traits, and Lifetimes Chapter 11: Writing Automated Tests Chapter 12: An I/O Project: Building a Command Line Program Chapter 13: Functional Language Features: Iterators and Closures Chapter 14: More About Cargo and Crates.io Chapter 15: Smart Pointers Chapter 16: Fearless Concurrency Chapter 17: Fundamentals of Asynchronous Programming: Async, Await, Futures, and Streams Chapter 18: Object-Oriented Programming Features Chapter 19: Patterns and Matching Chapter 20: Advanced Features Chapter 21: Final Project: Building a Multithreaded Web Server Appendix A: Keywords Appendix B: Operators and Symbols Appendix C: Derivable Traits Appendix D: Useful Development Tools Appendix E: Editions Index

Learn How to Code through Interactive Examples

Python Practice Lab

Quantum Process Algebra introduces readers to the algebraic properties and laws for quantum computing. The book provides readers with all aspects of algebraic theory for quantum computing, including the basis of semantics and axiomatization for quantum computing. With the assumption of a quantum system, readers will learn to solve the modelling of the three main components in a quantum system: unitary operator, quantum measurement, and quantum entanglement, with full support of quantum and classical computing in closed systems. Next, the book establishes the relationship between probabilistic quantum bisimilarity and classical probabilistic bisimilarity, including strong probabilistic bisimilarity and weak probabilistic bisimilarity, which makes an axiomatization of quantum processes possible. With this framework, quantum and classical computing mixed processes are unified with the same structured operational semantics. Finally, the book establishes a series of axiomatizations of quantum process algebras. These process algebras support nearly all main computation properties. Quantum and classical computing in closed quantum systems are unified with the same equational logic and the same structured operational semantics under the framework of ACP-like probabilistic process algebra. This unification means that the mathematics in the book can be used widely for verification of quantum and classical computing mixed systems, for example, most quantum communication protocols. ACP-like axiomatization also inherits the advantages of ACP, for example, and modularity means that it can be extended in an elegant way.

Quantum Process Algebra

Covering the three underlying technologies of Web pages: HTML, CSS, and JavaScript, this book is a one-stop guide to getting started in web development, be it in a class or as a solo-learner.

Covering the three underlying technologies of web pages—HTML, CSS, and JavaScript—this book is a one‑stop guide to getting started in web development, be it in a class or as a solo‑learner. Starting with no prerequisites beyond minimal exposure to programming, this book guides readers in an accessible fashion through modern page layout methods to building a complete site.This book develops an understanding of the structure of a page (how its parts fit together to convey its content to site users), how styles can make the content attractive and appealing, and how short programs and scripts can add everything from simple interactivity to complex calculations to your pages. With a wealth of in‑depth examples, review questions, exercises, and online sources and videos, readers are encouraged to excel in all of these areas, learning how to add animations, timing, designs that change in response to the characteristics of a display device, and more.Building knowledge from the ground up, this book appeals to those looking to learn web development from a range of backgrounds, be it academic, professional, or personal.

Developing Web Sites with HTML, CSS and JavaScript

Tcl/Tk: A Developer's Guide, Fourth Edition is an essential resource for computer professionals, from systems administrators to programmers. It covers new Tcl features, expanded Tcl-OO coverage, web technology using Rivet and SQLite, and AI integration with AWS. The book also delves into Tcl's standard tools, multi-faceted nature, and extensibility, making it ideal for developing GUIs, client/server middleware, and web applications. Readers will quickly learn to code in Tcl and extend its capabilities with the inclusion of numerous code examples and case studies. The updated edition includes over 150 pages on the latest Tcl extensions, proven techniques, and tools for effective programming. Extensive code snippets and online tutorials enhance understanding, while case studies provide practical insights. The book also discusses Tcl's role as the hidden "secret sauce" in commercial applications, highlighting its graphics and control infrastructure. With a vibrant user community and evolving API, Tcl/Tk remains a powerful and versatile programming platform for both beginners and experienced programmers.

A Developer's Guide

Tcl/Tk

Foundations, Technologies, and Prospects for the Future

Autonomous Vehicle Safety Solutions

Mastering Prompt Engineering: Deep Insights for Optimizing Large Language Models (LLMs) is a comprehensive guide that takes readers on a journey through the world of Large Language Models (LLMs) and prompt engineering. Covering foundational concepts, advanced techniques, ethical considerations, and real-world case studies, this book equips both novices and experts to navigate the complex LLM landscape. It provides insights into LLM architecture, training, and prompt engineering methods, while addressing ethical concerns such as bias and privacy. Real-world case studies showcase the practical application of prompt engineering in a wide range of settings. This resource is not just for specialists but is a practical and ethically conscious guide for AI practitioners, students, scientific researchers, and anyone interested in harnessing the potential of LLMs in natural language processing and generation. Mastering Prompt Engineering serves as a gateway to a deeper understanding of LLMs and their responsible and effective utilization through its comprehensive, ethical, and practical approach.

Deep Insights for Optimizing Large Language Models (LLMs)

Mastering Prompt Engineering

Probability for Deep Learning Quantum provides readers with the first book to address probabilistic methods in the deep learning environment and the quantum technological area simultaneously, by using a common platform: the Many-Sorted Algebra (MSA) view. While machine learning is created with a foundation of probability, probability is at the heart of quantum physics as well. It is the cornerstone in quantum applications. These applications include quantum measuring, quantum information theory, quantum communication theory, quantum sensing, quantum signal processing, quantum computing, quantum cryptography, and quantum machine learning. Although some of the probabilistic methods differ in machine learning disciplines from those in the quantum technologies, many techniques are very similar. Probability is introduced in the text rigorously, in Komogorov’s vision. It is however, slightly modified by developing the theory in a Many-Sorted Algebra setting. This algebraic construct is also used in showing the shared structures underlying much of both machine learning and quantum theory. Both deep learning and quantum technologies have several probabilistic and stochastic methods in common. These methods are described and illustrated using numerous examples within the text. Concepts in entropy are provided from a Shannon as well as a von-Neumann view. Singular value decomposition is applied in machine learning as a basic tool and presented in the Schmidt decomposition. Besides the in-common methods, Born’s rule as well as positive operator valued measures are described and illustrated, along with quasi-probabilities. Author Charles R. Giardina provides clear and concise explanations, accompanied by insightful and thought-provoking visualizations, to deepen your understanding and enable you to apply the concepts to real-world scenarios.

A Many-Sorted Algebra View

Probability for Deep Learning Quantum

Using Computational Thinking in Everyday Life

Problem Solving with Python

Covering the three underlying technologies of Web pages: HTML, CSS, and JavaScript, this book is a one-stop guide to getting started in web development, be it in a class or as a solo-learner.

Java Generics and Collections has been the go-to guide to generics for more than a decade. This second edition covers Java 21, providing a clear guide to generics from their most common uses to the strangest corner cases, giving you everything you need to know to use and write generic APIs effectively. It covers the collections library thoroughly, so you'll always know how and when to use each collection for any given task. And it explains stream processing, so you'll know which model to use and how they interoperate to get the best out of the platform library. This indispensable guide covers: <ul> <li>Fundamentals of generics: type parameters and generic methods </li><li>Subtyping and wildcards </li><li>Generics and reflection </li><li>Design patterns for generics </li><li>Sets, queues, lists, maps, and their implementations </li><li>Concurrent programming and thread safety with collections </li><li>Performance of different collection implementations </li><li>Best practices for using and extending the Java collections framework </li><li>Design philosophy and comparison with other collections libraries </li></ul>

Fundamentals and Recommended Practices

Java Generics and Collections

Python Fast Track: A Complete Guide to Rapidly Mastering and Applying Python Programming adopts a simplified writing style and provides clear explanations to ensure ease of understanding, making it an ideal resource for those new to Python. Starting with the basics, the book covers fundamental concepts such as variables, data types, printing and prompting, lists, dictionaries, tuples, control structure, functions, and object-oriented concepts. The book includes everything you need to understand and apply more advanced programming techniques such as file handling, exception handling, and regex. This great resource is created especially for those who want to apply Python for their research and professional work in scientific computing, data analysis and machine learning, including chapters on NumPy and Pandas, two of the most popular Python application libraries. It demonstrates how to effectively master key applications of Python such as web development, software creation, task automation, and data analysis. The book covers data analysis and machine learning tasks that greatly benefit from Python, thanks to libraries such as TensorFlow and Keras that enable efficient coding.

A Complete Guide to Rapidly Mastering and Applying Python Programming

Python Fast Track

The Linux Memory Manager

The Rust Programming Language, 3rd Edition

Bibliografische Angaben

Inhaltsverzeichnis

Schlagworte

Bibliografische Angaben

Inhaltsverzeichnis

Schlagworte

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