Название: Python Asynchronous Web Development with asyncio: No more waiting screens or unresponsive interfaces! Write clean, maintainable code that prioritizes readability. Build Scalable Applications, conquer Starlette, Quart and more!
Автор: Каtiе Мilliе
Издательство: Independently published
Серия: Python Trailblazer’s Bible
Год: 2024
Страниц: 188
Язык: английский
Формат: pdf
Размер: 32.7 MB

Tired of Laggy Web Apps? Unleash Python's Asynchronous Power: Build Blazing-Fast, Engaging Experiences (Even if You're New!). In today's hyper-connected world, users demand instantaneous web experiences. But traditional web development often struggles to keep up, leaving users frustrated with slow loading times and unresponsive interfaces. There's a better way: Python Asynchronous Web Development with asyncio. This book is your launchpad to building the next generation of web applications. We'll equip you with the skills to master asyncio, a revolutionary library that lets your applications handle multiple user requests simultaneously. The result? Web applications that feel instant, even under heavy traffic. Effortless Responsiveness: Build applications that feel lightning-fast! No more waiting screens or unresponsive interfaces. Your users will be delighted with the instant experience, keeping them engaged and coming back for more. Unleash Python's True Potential: Combine the elegance of Python with the speed of asynchronous programming. Write clean, maintainable code that prioritizes readability while achieving unparalleled performance. Become an In-Demand Developer: Asynchronous programming is a highly sought-after skill in the ever-growing web development landscape. This book prepares you with the knowledge and experience to stand out from the crowd and land your dream job.

Название: Ethical Hacking with Python: Developing Cybersecurity Tools
Автор: Nаtе Рhоеtеаn
Издательство: Independently published
Год: 2024
Страниц: 432
Язык: английский
Формат: pdf
Размер: 38.5 MB

Dive into the world of cybersecurity with "Ethical Hacking with Python: Developing Cybersecurity Tools," a comprehensive guide designed to elevate your skills in protecting digital assets against ever-evolving threats. This book meticulously unfolds the landscape of ethical hacking and the pivotal role Python plays in it, offering a deep dive into the art and science of identifying vulnerabilities, exploiting them ethically, and securing systems more robustly. From setting up your own ethical hacking lab with Python to mastering network scanning, vulnerability assessment, exploitation techniques, and beyond, this guide leaves no stone unturned. Each chapter is crafted with detailed explanations, practical demonstrations, and real-world scenarios, ensuring you gain both the theoretical knowledge and hands-on experience needed to thrive in the complex realm of cybersecurity. Whether you're a cybersecurity professional seeking to deepen your expertise, a computer science student aiming to complement your education with practical skills, or a programming enthusiast curious about ethical hacking, this book is your gateway to advancing your capabilities. Embrace the opportunity to develop your own Python tools and scripts, and position yourself at the forefront of cybersecurity efforts in a world teeming with digital challenges.

Название: PYTHON без проблем. Решаем реальные задачи и пишем полезный код
Автор: Даниэль Зингаро
Издательство: Питер
Год: 2023
ISBN: 978-5-4461-1920-2
Страниц: 337
Формат: PDF
Размер: 10 Mб
Язык: Русский

Даниэль Зингаро создал книгу для начинающих, чтобы вы сразу учились решать интересные задачи, которые использовались на олимпиадах по программированию, и развивали мышление программиста. В каждой главе вам даются задания, собственные решения можно выложить на сайт и получить оценку профи. Вы на практике освоите основные возможности, функции и методы языка Python и получите четкое представление о структурах данных, алгоритмах и других основах программирования.

Название: Computational Stochastic Programming: Models, Algorithms, and Implementation
Автор: Lеwis Ntаimо
Издательство: Springer
Год: 2024
Страниц: 518
Язык: английский
Формат: pdf (true), epub
Размер: 40.5 MB

This book provides a foundation in stochastic, linear, and mixed-integer programming algorithms with a focus on practical computer algorithm implementation. The purpose of this book is to provide a foundational and thorough treatment of the subject with a focus on models and algorithms and their computer implementation. The book’s most important features include a focus on both risk-neutral and risk-averse models, a variety of real-life example applications of stochastic programming, decomposition algorithms, detailed illustrative numerical examples of the models and algorithms, and an emphasis on computational experimentation. With a focus on both theory and implementation of the models and algorithms for solving practical optimization problems, this monograph is suitable for readers with fundamental knowledge of linear programming, elementary analysis, probability and statistics, and some computer programming background. Several examples of stochastic programming applications areincluded, providing numerical examples to illustrate the models and algorithms for both stochastic linear and mixed-integer programming, and showing the reader how to implement the models and algorithms using computer software.

Название: Methodologies, Frameworks, and Applications of Machine Learning
Автор: Рrаmоd Кumаr Srivаstаvа, Аshоk Кumаr Yаdаv
Издательство: IGI Global
Год: 2024
Страниц: 315
Язык: английский
Формат: pdf (true), epub
Размер: 36.4 MB

In the ever-evolving landscape of technology, Machine Learning stands as a beacon of innovation with the potential to reshape industries and redefine our daily lives. As editors of this comprehensive reference book, Methodologies, Frameworks, and Applications of Machine Learning, we are thrilled to present a compendium that encapsulates the essence of the latest advancements, theoretical foundations, and practical applications in the realm of Machine Learning. Technology is constantly evolving, and Machine Learning is positioned to become a pivotal tool with the power to transform industries and revolutionize everyday life. This book underscores the urgency of leveraging the latest Machine Learning methodologies and theoretical advancements, all while harnessing a wealth of realistic data and affordable computational resources. Machine Learning is no longer confined to theoretical domains; it is now a vital component in healthcare, manufacturing, education, finance, law enforcement, and marketing, ushering in an era of data-driven decision-making. The Chapter 2 focuses on practical implementations of Machine Learning projects using Scikit-learn and TensorFlow libraries in Python. Four distinct projects unfold, each addressing classification, regression, and image classification problems. The step-by-step walkthrough covers model evaluation using classical Machine Learning techniques and deep neural networks.

Название: javascript Essentials For Dummies
Автор: Раul МсFеdriеs
Издательство: For Dummies
Год: 2024
Страниц: 192
Язык: английский
Формат: pdf, epub (true), mobi
Размер: 10.1 MB

The concise and digestible get-started guide to javascript programming. javascript Essentials For Dummies is your quick reference to all the core concepts about javascript—the dynamic scripting language that is often the final step in creating powerful websites. This no-nonsense book gets right to the point, eliminating review material, wordy explanations, and fluff. Find out all you need to know about the foundations of javascript, swiftly and crystal clear. Perfect for a brush-up on the basics or as an everyday desk reference on the job, this is the reliable little book you can always turn to for answers. What’s the difference between a page that does nothing and a page that seems to be always dancing? One word: javascript. If you want your pages to be dynamic and interactive, you need a bit of behind-the-scenes javascript to make it so. “But,” I hear you object, “HTML isn’t that hard to learn. javascript is a programming language, for crying out loud!” I hear you. I believe that if you begin with the basic syntax and rules, study tons of examples to learn how they work, and then slowly build up to more complex scripts, you can learn javascript programming. I predict here and now that by the time you finish this book, you’ll even be a little bit amazed at yourself and at what you can do. This book is to the point, focusing on the key topics you need to know about this popular programming language. Great for supplementing classroom learning, reviewing for a certification, or staying knowledgeable on the job.

Название: Large Language Model-Based Solutions: How to Deliver Value with Cost-Effective Generative AI Applications
Автор: Shreyas Subramanian
Издательство: Wiley
Год: 2024
Страниц: 224
Язык: английский
Формат: epub (true)
Размер: 15.5 MB

Learn to build cost-effective apps using Large Language Models. In Large Language Model-Based Solutions: How to Deliver Value with Cost-Effective Generative AI Applications, Principal Data Scientist at Amazon Web Services, Shreyas Subramanian, delivers a practical guide for developers and data scientists who wish to build and deploy cost-effective large language model (LLM)-based solutions. In the book, you'll find coverage of a wide range of key topics, including how to select a model, pre- and post-processing of data, prompt engineering, and instruction fine tuning. Large language models (LLMs) have become a cornerstone of Artificial Intelligence (AI) research and applications, transforming the way we interact with technology and enabling breakthroughs in natural language processing (NLP). The author sheds light on techniques for optimizing inference, like model quantization and pruning, as well as different and affordable architectures for typical generative AI (GenAI) applications, including search systems, agent assists, and autonomous agents. Perfect for developers and data scientists interested in deploying foundational models, or business leaders planning to scale out their use of GenAI, Large Language Model-Based Solutions will also benefit project leaders and managers, technical support staff, and administrators with an interest or stake in the subject.

Название: Python All-in-One For Dummies, 3rd Edition
Автор: Jоhn Shоviс, Аlаn Simрsоn
Издательство: For Dummies
Год: 2024
Страниц: 704
Язык: английский
Формат: epub (true)
Размер: 38.2 MB

Everything you need to know to get into Python coding, with 7 books in one. Python All-in-One For Dummies is your one-stop source for answers to all your Python questions. From creating apps to building complex web sites to sorting big data, Python provides a way to get the work done. This book is great as a starting point for those new to coding, and it also makes a perfect reference for experienced coders looking for more than the basics. Apply your Python skills to data analysis, learn to write AI-assisted code using GitHub CoPilot, and discover many more exciting uses for this top programming language. This book is a reference manual to guide you through the process of learning Python and how to use it in modern computer applications, such as data science, artificial intelligence, physical computing, and robotics. If you're looking to learn a little about a lot of exciting things, this is the book for you. It gives you an introduction to the topics that you'll need to explore more deeply. Python All-in-One For Dummies, 3rd Edition guides you through the Python language and then takes you on a tour through some cool libraries and technologies (the Raspberry Pi, robotics, AI, Data Science, and more) that all revolve around the Python language. When you work on new projects and new technologies, Python is there with a diverse number of libraries just waiting for you to use.

Название: Jetpack Compose 1.5 Essentials: Developing Android Apps with Jetpack Compose 1.5, Android Studio, and Kotlin
Автор: Nеil Smуth
Издательство: Payload Media, Inc.
Год: 2024
Страниц: 636
Язык: английский
Формат: epub
Размер: 10.5 MB

This book teaches you how to build Android applications using Jetpack Compose 1.5, Android Studio Hedgehog (2023.1.1), Material Design 3, and the Kotlin programming language. The book begins with the basics by explaining how to set up an Android Studio development environment. The book also includes in-depth chapters introducing the Kotlin programming language, including data types, operators, control flow, functions, lambdas, coroutines, and object-oriented programming. If you are new to Kotlin programming, the entire book is appropriate for you. An introduction to the key concepts of Jetpack Compose and Android project architecture is followed by a guided tour of Android Studio in Compose development mode. The book also covers the creation of custom Composables and explains how functions are combined to create user interface layouts, including row, column, box, flow, pager, and list components. Other topics covered include data handling using state properties and key user interface design concepts such as modifiers, navigation bars, and user interface navigation. Additional chapters explore building your own reusable custom layout components, securing your apps with Biometric authentication, and integrating Google Maps. The book covers graphics drawing, user interface animation, transitions, Kotlin Flows, and gesture handling.

Название: Robust Machine Learning Distributed Methods for Safe AI
Автор: Rасhid Guеrrаоui, Niruраm Guрta, Rаfаеl Рinоt
Издательство: Springer
Серия: Machine Learning: Foundations, Methodologies, and Applications
Год: 2024
Страниц: 180
Язык: английский
Формат: pdf, epub
Размер: 10.1 MB

Today, Machine Learning algorithms are often distributed across multiple machines to leverage more computing power and more data. However, the use of a distributed framework entails a variety of security threats. In particular, some of the machines may misbehave and jeopardize the learning procedure. This could, for example, result from hardware and software bugs, data poisoning or a malicious player controlling a subset of the machines. This book explains in simple terms what it means for a distributed Machine Learning scheme to be robust to these threats, and how to build provably robust Machine Learning algorithms. Studying the robustness of Machine Learning algorithms is a necessity given the ubiquity of these algorithms in both the private and public sectors. Accordingly, over the past few years, we have witnessed a rapid growth in the number of articles published on the robustness of distributed Machine Learning algorithms. We believe it is time to provide a clear foundation to this emerging and dynamic field. By gathering the existing knowledge and democratizing the concept of robustness, the book provides the basis for a new generation of reliable and safe Machine Learning schemes. In addition to introducing the problem of robustness in modern Machine Learning algorithms, the book will equip readers with essential skills for designing distributed learning algorithms with enhanced robustness. This book is intended for students, researchers, and practitioners interested in AI systems in general, and in Machine Learning schemes in particular. The book requires certain basic prerequisites in linear algebra, calculus, and probability. Some understanding of computer architectures and networking infrastructures would be helpful.