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Название: Python-Powered Ethical Hacking: Building Advanced Cybersecurity Tools
Автор: Peter Johnson
Издательство: HiTeX Press
Год: 2024
Страниц: 499
Язык: английский
Формат: pdf, epub, mobi
Размер: 10.1 MB

"Python-Powered Ethical Hacking: Building Advanced Cybersecurity Tools" serves as a comprehensive guide for aspiring and seasoned ethical hackers alike. This book meticulously combines the foundational principles of ethical hacking with the powerful capabilities of Python, offering readers a profound understanding of how to detect, analyze, and mitigate cybersecurity threats. Each chapter is thoughtfully structured to provide both theoretical insights and practical applications, ensuring a well-rounded learning experience. From setting up a secure hacking environment to developing custom exploits and performing advanced forensics, the content is tailored to equip readers with the skills necessary to navigate the complexities of modern cybersecurity challenges. Throughout the book, readers will find detailed explanations, code snippets, and real-world case studies that illustrate the effective use of Python in various hacking scenarios. The emphasis on legal and ethical considerations underscores the importance of responsible hacking practices. Whether you are a beginner eager to step into the world of ethical hacking or a professional looking to enhance your skill set with Python, this book offers invaluable knowledge and tools to strengthen your cybersecurity arsenal and contribute to a safer digital environment. Ethical hacking, also known as penetration testing or white-hat hacking, plays a critical role in maintaining the security of information systems. In a world where cybersecurity threats are constantly evolving, the need for skilled professionals equipped with the knowledge and tools to detect vulnerabilities and foresee potential security breaches has never been more pressing. Among the various tools available, Python stands out for its simplicity, versatility, and powerful libraries that facilitate the creation of a wide range of hacking and security tools.

Название: Информатика и программирование: объектно-ориентированное программирование (на основе языка С#)
Автор: Мурадханов С.Э., Широков А.И.
Издательство: Издательский Дом МИСиС
Год: 2015
Cтраниц: 309
Формат: pdf
Размер: 31 мб
Язык: русский

Объектно-ориентированная парадигма (ОПП) является фундаментом разработки современных программных комплексов. Изучающая такие средства дисциплина имеет как теоретическую составляющую (объектно-ориентированный подход к анализу предметной области), так и практическую (синтез информационной системы с использованием инструментов объектно-ориентированной разработки).

Название: R Programming for Data Science: A comprehensive guide to R programming for Data Science
Автор: Et Tu Code
Издательство: Independently published
Год: 2024
Страниц: 283
Язык: английский
Формат: pdf, epub, mobi
Размер: 10.6 MB

Welcome to "R Programming for Data Science", a comprehensive guide that will take you on a journey from the basics of R programming to advanced techniques for working with data in the context of Data Science. As someone interested in Data Science, you're likely aware of the importance of having a strong foundation in programming and data manipulation skills. This book aims to provide you with just that, using R as the primary tool for exploring and analyzing data. R has emerged as one of the most popular languages for data analysis and visualization, and for good reason. Its flexibility, ease of use, and extensive library of packages make it an ideal choice for anyone looking to extract insights from large datasets. Whether you're a student, researcher, or professional in the field of Data Science, R is an essential tool that will help you get the job done. This book is designed to be both comprehensive and accessible, covering topics such as data types, visualization, statistical modeling, and Machine Learning. You'll learn how to work with datasets, manipulate and transform data, create visualizations, and build predictive models using popular R packages like dplyr, tidyr, ggplot2, caret, and more. Throughout the book, we'll focus on practical applications of R programming concepts, using real-world examples and case studies to illustrate key ideas. You'll also learn how to troubleshoot common errors, work with missing data, and optimize your code for efficiency. This book is intended for anyone interested in Data Science, regardless of their prior programming experience.

Название: Split Federated Learning for Secure IoT Applications: Concepts, frameworks, applications and case studies
Автор: Gururaj Harinahalli Lokesh, Geetabai S. Hukkeri, N.Z. Jhanjhi, Hong Lin
Издательство: The Institution of Engineering and Technology
Год: 2024
Страниц: 285
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

New approaches in Federated Learning and Split Learning have the potential to significantly improve ubiquitous intelligence in Internet of Things (IoT) applications. In Split Federated Learning, the Machine Learning model is divided into smaller network segments, with each segment trained independently on a server using distributed local client data. The split learning method mitigates two fundamental drawbacks of Federated Learning: affordability, and privacy and security. When running Machine Learning computation on devices with limited resources, assigning only a portion of the network to train at the client-side minimizes the processing burden, compared to running a complete network as in Federated Learning. In addition, neither client nor server has full access to the other, which is more secure. This book reviews cutting edge technologies and advanced research in Split Federated Learning. Coverage includes approaches to realizing and evaluating the effectiveness and advantages of Federated Learning and Splitfed learning, the role of this technology in advancing and securing IoTs, advanced research on emerging AI models for preserving the privacy of the data owned by the clients, and the analysis and development of AI mechanisms in IoT architectures and applications. The use of Split Federated Learning in natural language processing (NLP), recommendation systems, healthcare systems, emotion detection, smart agriculture, smart transportation and smart cities is discussed. The authors of Chapter 1 elaborate on the fundamentals of Federated Learning (FL) and Split Learning which are the two common approaches to distributed Machine Learning. This book offers useful insights to the latest developments in the field for researchers, engineers and scientists in academia and industry, who are working in computing, AI, Data Science and cybersecurity with a focus on Federated Learning, Machine Learning and Deep Learning.

Название: Introduction to Python and Large Language Models: A Guide to Language Models
Автор: Dilyan Grigorov
Издательство: Apress
Год: 2024
Страниц: 395
Язык: английский
Формат: pdf, epub
Размер: 10.1 MB

Gain a solid foundation for Natural Language Processing (NLP) and Large Language Models (LLMs), emphasizing their significance in today’s computational world. This book is an introductory guide to NLP and LLMs with Python programming. The book starts with the basics of NLP and LLMs. It covers essential NLP concepts, such as text preprocessing, feature engineering, and sentiment analysis using Python. The book offers insights into Python programming, covering syntax, data types, conditionals, loops, functions, and object-oriented programming. Next, it delves deeper into LLMs, unraveling their complex components. You’ll learn about LLM elements, including embedding layers, feedforward layers, recurrent layers, and attention mechanisms. You’ll also explore important topics like tokens, token distributions, zero-shot learning, LLM hallucinations, and insights into popular LLM architectures such as GPT-4, BERT, T5, PALM, and others. Additionally, it covers Python libraries like Hugging Face, OpenAI API, and Cohere. The final chapter bridges theory with practical application, offering step-by-step examples of coded applications for tasks like text generation, summarization, language translation, question-answering systems, and chatbots. In the end, this book will equip you with the knowledge and tools to navigate the dynamic landscape of NLP and LLMs. For data analysts, AI and Machine Learning Experts, Python developers, and Software Development Professionals interested in learning the foundations of NLP, LLMs, and the processes of building modern LLM applications for various tasks.

Название: GitHub Actions in Action (Final)
Автор: Michael Kaufmann
Издательство: Manning Publications
Год: 2024
Страниц: 257
Язык: английский
Формат: pdf (true)
Размер: 31.9 MB

Automate your build, test, and deploy pipelines using GitHub Actions! Continuous delivery (CI/CD) pipelines help you automate the software development process and maximize your team’s efficiency. GitHub Actions in Action teaches you to build real-world build, test, and deploy pipelines in GitHub Actions through hands-on labs and projects. GitHub Actions in Action is filled with battle-tested methods for automating delivery pipelines and delivering features faster. DevOps engineers will love the coverage of reliable methods for Infrastructure-as-Code and automating cloud environments. Written by three Microsoft MVPs and tech reviewed by a Staff DevOps Architect from GitHub, this book delivers the hardworking skills and advice you’ll need to be successful on the job. GitHub Actions in Action shows you exactly how to implement a secure and reliable continuous delivery process with just the tools available in GitHub—no complex CI/CD frameworks required! You’ll follow an extended example application for selling tickets, taking it all the way from initial build to cloud deployment. The first part of the book introduces the basics of workflows and actions, all illustrated with simple examples. You’ll then move on to the platform’s architecture, security considerations, and in-depth coverage of the workflow runtime. Finally, you’ll learn how to deliver a complete CI/CD pipeline, including compliance and performance and costs optimization. You’ll even learn to create your own actions that you can share in the GitHub marketplace! For software developers and DevOps engineers already working with GitHub and looking to expand to GitHub Actions.

Название: Applied Swarm Intelligence
Автор: Yaniv Altshuler
Издательство: CRC Press
Год: 2025
Страниц: 341
Язык: английский
Формат: pdf (true), epub
Размер: 42.1 MB

This book provides a comprehensive analysis of the tools and techniques used today for designing and modeling of efficient and robust Swarm Intelligence based systems: highly (or fully) decentralized, semi-autonomous, highly-scalable infrastructures in various real-life scenarios. Among others, the book reviews the use of the Swarm Intelligence paradigm in financial investment, blockchain protocols design, shared transportation systems, communication networks, bioinformatics, and military applications. Theoretical and practical limitations of such systems, as well as trade-offs between the various economic and operational parameters of the systems, are discussed. The book is intended for researchers and engineers in the fields of swarm systems, economics, agriculture, nutrition, and operation research. Provides a comprehensive analysis of the tools and techniques used for the development of efficient and robust decentralized infrastructures for various real-life scenarios, ranging from financial investment through blockchain protocols, shared transportation systems and communication networks, to bioinformatics and military applications. The target audience for this work includes academic researchers, industry professionals, and enthusiasts in the fields of Computer Science, robotics, and Artificial Intelligence. It is structured to provide both depth and breadth in understanding Swarm Intelligence, making it accessible to newcomers while still offering valuable insights for seasoned experts. This book is more than just an academic text; it is a call to rethink how we approach problem-solving and innovation in the age of AI. It invites you, the reader, to explore how the principles of Swarm Intelligence can be applied to your own work, potentially transforming challenges into opportunities. Enjoy your journey through the intriguing world of AI and Swarm Intelligence.

Название: Artificial Intelligence For Dummies, 3rd Edition
Автор: John Paul Mueller, Luca Massaron, Stephanie Diamond
Издательство: For Dummies
Год: 2025
Страниц: 344
Язык: английский
Формат: pdf, epub
Размер: 10.1 MB

Dive into the intelligence that powers Artificial Intelligence (AI). Artificial Intelligence is swiftly moving from a sci-fi future to a modern reality. This edition of Artificial Intelligence For Dummies keeps pace with the lighting-fast expansion of AI tools that are overhauling every corner of reality. This book demystifies how artificial intelligence systems operate, giving you a look at the inner workings of AI and explaining the important role of data in creating intelligence. You'll get a primer on using AI in everyday life, and you'll also get a glimpse into possible AI-driven futures. What's next for humanity in the age of AI? How will your job and your life change as AI continue to evolve? How can you take advantage of AI today to make your live easier? This jargon-free Dummies guide answers all your most pressing questions about the world of Artificial Intelligence. Artificial Intelligence For Dummies is the ideal starting point for anyone seeking a deeper technological understanding of how artificial intelligence works and what promise it holds for the future.

Название: Python Programming for Beginners: Mastering Python with No Prior Experience: The Ultimate Guide to Conquer Your Coding Fears from Crash and Land Your First Job in Tech
Автор: Antonio Webber
Издательство: Independently published
Год: 2024
Страниц: 204
Язык: английский
Формат: pdf, epub (true)
Размер: 10.1 MB

Learn Python Programming Fast - A Beginner's Guide to Mastering Python from Home. Python is the most in-demand programming language in 2024. As a beginner, learning Python can open up high-paying remote and freelance job opportunities in fields like Data Science, web development, AI, and more. This hands-on Python Programming is designed specifically for beginners with no prior coding experience. It provides a foundations-first introduction to Python programming concepts using simplified explanations, practical examples, and step-by-step tutorials. Programming is best learned by doing, and thus, this book incorporates numerous practical exercises and real-world projects. This is not Hype; you will learn something new in this Python Programming for Beginners. Python stands out as a highly favored programming language globally, valued for its utility, accessibility, and widespread applicability across diverse fields such as web development, data analysis, and Artificial Intelligence. Whether you're starting from scratch or an adept coder seeking to broaden your expertise, embracing Python presents a gateway to myriad opportunities. A wide library ecosystem more enhances Python's appeal. The built-in Python Standard Library, coupled with third-party libraries like NumPy, Pandas, and Django, equips users with a wealth of pre-built tools for tasks spanning scientific computing, data analysis, and web development. Python's resourcefulness is evident in its ability to handle various applications, including the development of web applications, task automation, data analysis, and the creation of Machine Learning models. Its cross-platform compatibility enables smooth code execution across diverse operating systems.

Название: Computational Intelligence: Theory and Applications
Автор: T. Ananth Kumar, E. Golden Julie, Venkata Raghuveer Burugadda, Abhishek Kumar
Издательство: Wiley-Scrivener
Год: 2025
Страниц: 396
Язык: английский
Формат: pdf (true)
Размер: 36.4 MB

This book provides a comprehensive exploration of Computational Intelligence (CI) techniques and their applications, offering valuable insights into advanced information processing, Machine Learning concepts, and their impact on agile manufacturing systems. Computational Intelligence presents a new concept for advanced information processing. Computational Intelligence (CI) is the principle, architecture, implementation, and growth of Machine Learning concepts that are physiologically and semantically inspired. Computational Intelligence methods aim to develop an approach to evaluating and creating flexible processing of human information, such as sensing, understanding, learning, recognizing, and thinking. The Artificial Neural Network simulates the human nervous system's physiological characteristics and has been implemented numerically to non-linear mapping. Fuzzy Logic Systems simulate the human brain's psychological characteristics and have been used for linguistic translation through membership functions and bioinformatics. The Genetic Algorithm simulates computer evolution and has been applied to solve problems with optimization algorithms for improvements in diagnostic and treatment technologies for various diseases. To expand the agility and learning capacity of manufacturing systems, these methods play essential roles. This book will express the computer vision techniques that make manufacturing systems more flexible, efficient, robust, adaptive, and productive by examining many applications and research into Computational Intelligence techniques concerning the main problems in design, making plans, and manufacturing goods in agile manufacturing systems.