Название: Federated Learning Systems: Towards Privacy-Preserving Distributed AI
Автор: Muhammad Habib ur Rehman, Mohamed Medhat Gaber
Издательство: Springer
Серия: Studies in Computational Intelligence
Год: 2025
Страниц: 179
Язык: английский
Формат: pdf (true), epub
Размер: 19.3 MB

This book dives deep into both industry implementations and cutting-edge research driving the Federated Learning (FL) landscape forward. FL enables decentralized model training, preserves data privacy, and enhances security without relying on centralized datasets. Industry pioneers like NVIDIA have spearheaded the development of general-purpose FL platforms, revolutionizing how companies harness distributed data. Alternately, for medical AI, FL platforms, such as FedBioMed, enable collaborative model development across healthcare institutions to unlock massive value. Research advances in PETs highlight ongoing efforts to ensure that FL is robust, secure, and scalable. Looking ahead, Federated Learning could transform public health by enabling global collaboration on disease prevention while safeguarding individual privacy. From recommendation systems to cybersecurity applications, FL is poised to reshape multiple domains, driving a future where collaboration and privacy coexist seamlessly.

Название: Engineering Elixir Applications: Navigate Each Stage of Software Delivery with Confidence
Автор: Ellie Fairholm, Josep Giralt D’Lacoste
Издательство: Pragmatic Bookshelf
Год: 2025
Страниц: 450
Язык: английский
Формат: pdf (true), epub
Размер: 19.1 MB

The days of separate dev and ops teams are over - knowledge silos and the "throw it over the fence" culture they create are the enemy of progress. As an engineer or developer, you need to confidently own each stage of the software delivery process. This book introduces a new paradigm, BEAMOps, that helps you build, test, deploy, and debug BEAM applications. Create effective development and deployment strategies; leverage continuous improvement pipelines; and ensure environment integrity. Combine operational orchestrators such as Docker Swarm with the distribution, fault tolerance, and scalability of the BEAM, to create robust and reliable applications. BEAMOps starts by building a solid foundation for your project. On the infrastructure side, see how to use Terraform before you even start coding to automate your deployment and operations. On the project management side, we show you how to use issues and milestones to simplify tracking; you'll use this foundation as you go through the book, implementing each of the steps required to deploy a scalable Elixir application.

Название: Advances in Optimization Algorithms for Multidisciplinary Engineering Applications
Автор: Diego Oliva, Arturo Valdivia, Seyed Jalaleddin Mousavirad, Kanak Kalita
Издательство: Springer
Серия: Studies in Computational Intelligence
Год: 2025
Страниц: 798
Язык: английский
Формат: pdf (true)
Размер: 48.9 MB

This book is an authoritative compilation of the latest advancements in optimization techniques. This book covers a wide array of methods ranging from classical to metaheuristic to AI-enhanced approaches. The chapters are meticulously selected and organized in three sections—metaheuristics, Machine Learning and engineering applications. This allows for an in-depth exploration of diverse topics ranging from image processing to feature selection to data clustering, to practical applications like energy optimization, smart grids, healthcare diagnostics, etc. Each chapter delves into the specific algorithms and applications as well as provides ample theoretical insights. Accordingly, this book is ideally suited for undergraduate and postgraduate students in fields such as science, engineering and computational mathematics. It is also an invaluable resource for courses on Artificial Intelligence, Computational Intelligence, etc. Researchers and professionals in evolutionary computation, Artificial Intelligence and engineering will find the material especially useful for advancing their work and exploring new frontiers in optimization.

Название: Python From Zero to Hero: Volume 1-4
Автор: Maxwell Innovations
Издательство: Maxwell Innovations
Год: 2024
Страниц: 824+209+281+217
Язык: английский
Формат: epub
Размер: 10.1 MB

Unlock the Secrets of Python Mastery with This Ultimate Guide! Are you ready to skyrocket your Python programming skills and become a coding superstar? Look no further! This comprehensive, all-in-one book is your ticket to mastering Python, whether you're a complete beginner or an experienced coder looking to up your game. As you reach the conclusion of this guide, you have gained a solid foundation in Python programming, from understanding basic syntax to building complex projects. However, learning is an ongoing journey, especially in the ever-evolving field of programming. This final chapter is designed to help you transition from a learner to a practitioner who continually grows and contributes to the Python community. We'll explore best practices that will elevate the quality of your code, provide resources to further expand your knowledge, and guide you on how to become an active member of the vibrant Python ecosystem.

Название: Federated Cyber Intelligence: Federated Learning for Cybersecurity
Автор: Hamed Tabrizchi, Ali Aghasi
Издательство: Springer
Серия: SpringerBriefs in Computer Science
Год: 2025
Страниц: 119
Язык: английский
Формат: pdf (true), epub (true), mobi
Размер: 10.1 MB

This book offers a detailed exploration of how Federated Learning can address critical challenges in modern cybersecurity. It begins with an introduction to the core principles of Federated Learning (FL). Then it highlights a strong foundation by exploring the fundamental components, workflow, and algorithms of Federated Learning, alongside its historical development and relevance in safeguarding digital systems. The subsequent sections offer insight into key cybersecurity concepts, including confidentiality, integrity, and availability. It also offers various types of cyber threats, such as malware, phishing, and advanced persistent threats. This book provides a practical guide to applying Federated Learning in areas such as intrusion detection, malware detection, phishing prevention, and threat intelligence sharing. It examines the unique challenges and solutions associated with this approach, such as data heterogeneity, synchronization strategies and privacy-preserving techniques.

Название: Neural Network Algorithms and Their Engineering Applications
Автор: Chao Huang, Hailong Huang, Yiying Zhang
Издательство: Morgan Kaufmann/Elsevier
Год: 2025
Страниц: 244
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

Neural Network Algorithms and Their Engineering Applications presents the relevant techniques used to improve the global search ability of neural network algorithms in solving complex engineering problems with multimodal properties. The book provides readers with a complete study of how to use artificial neural networks to design a population-based metaheuristic algorithm, which in turn promotes the application of artificial neural networks in the field of engineering optimization. The authors provide a deep discussion for the potential application of Machine Learning methods in improving the optimization performance of the neural network algorithm, helping readers understand how to use Machine Learning methods to design improved versions of the algorithm. Users will find a wealth of source code that covers all applied algorithms. Code applications enhance readers' understanding of methods covered and facilitate readers' ability to apply the algorithms to their own research and development projects.

Название: Automating Cybersecurity With Python
Автор: Riley Macaulay
Издательство: Riley Macaulay
Год: 2024
Формат: pdf
Страниц: 168
Размер: 20,11 Мб
Язык: английский

Drowning in Repetitive Security Tasks? Automate Your Way Out with Python! Imagine Albert, a cybersecurity analyst crushed by endless logs, server configs, and manual scans. Strategic defense? A distant dream. Then, Python entered her scene. With a few lines of code, Albert automated the mundane. Scripts scanned networks, analyzed logs, and deployed updates – all while he focused on real threats. Success bred success. The entire team embraced Python, freeing them to become proactive hunters. Attacks plummeted, replaced by a culture of strategic defense.

Название: Учись писать, читать и понимать алгоритмы: Алгоритмы для правильного мышления, Основы алгоритмизации
Автор: Владимир Паронджанов
Издательство: Москва
Год: 2012
Формат: pdf/djvu
Размер: 31 Мб
Cтраниц: 520, ил.
Язык: русский

Излагаются новые полезные для практики идеи и достижения, помогающие легко и быстро освоить алгоритмы. Дается систематизированное изложение основных понятий и методов алгоритмизации.

Название: Natural Language Processing with Python Updated Edition: From Basics to Advanced Projects: Mastering Text Analysis, Machine Learning Models, and Chatbot Development (Mastering the AI Revolution)
Автор: Cuantum Technologies
Издательство: Cuantum Technologies
Год: 2024
Страниц: 599
Язык: английский
Формат: True/Retail PDF, True/Retail EPUB
Размер: 20.7 MB

Are you fascinated by the power of language and eager to harness its potential using cutting-edge technology? Do you want to transform raw text data into valuable insights, build intelligent systems, and stay ahead in the rapidly evolving field of Natural Language Processing (NLP)? Look no further! this book is here to equip you with the knowledge and skills you need to excel in NLP. The purpose of this book is to provide a comprehensive, hands-on guide to Natural Language Processing using Python. NLP is a vast and complex field, and our aim is to cover a broad spectrum of topics, from the basics to advanced techniques, in a way that is both accessible and practical. This book aims to provide a practical and hands-on approach to starting with Mastering the Creative Power of AI. Whether you are a beginner without programming experience or an experienced programmer looking to expand your skills, this book is designed to help you develop your skills and build a solid foundation in Generative Deep Learning with Python.

Название: Mastering NumPy: The Ultimate Guide to Data Manipulation in Python
Автор: Muslum Yildiz
Издательство: Independently published
Год: October 21, 2024
Страниц: 280
Язык: английский
Формат: epub
Размер: 40.6 MB

Step into the future of data science and artificial intelligence with "Mastering NumPy: The Ultimate Guide to Data Manipulation in Python". This book is not just another technical guide; it’s your gateway to unlocking the full power of NumPy, the engine behind Python’s dominance in data processing, AI, and scientific computing. Whether you're a novice or a seasoned professional, this comprehensive resource takes you on a journey from mastering the basics to understanding the most advanced features of NumPy. Imagine transforming massive datasets, running complex computations, and building sophisticated AI models—all with the unparalleled speed and efficiency that NumPy provides. The book covers essential topics such as array manipulations, matrix operations, vectorized calculations, and advanced statistical functions, all designed to enhance your understanding of data manipulation in Python. Each chapter is packed with real-world examples, hands-on exercises, and expert insights that will deepen your mastery of NumPy. From array slicing and indexing to performing statistical analysis and random matrix generation, this guide is your key to becoming a NumPy expert.