Название: Ada Programming: Reliable, Strongly-Typed Systems Programming
Автор: Theophilus Edet
Издательство: CompreQuest Books
Год: 2024
Страниц: 769
Язык: английский
Формат: pdf, epub, mobi
Размер: 10.1 MB

Ada Programming: Reliable, Strongly-Typed Systems Programming offers an in-depth exploration of Ada, a language renowned for its reliability, robustness, and versatility in systems programming. Whether you're a seasoned developer or just beginning your journey, this comprehensive guide will help you master Ada and its unique features through a comprehensive set of essential constructs of Variables, Functions, Conditions, Collections, Loops, Comments, Enums, Classes, Accessors, and Scope, as well as the Ada's strong support for implementations of Concurrent Programming, Object-Oriented Programming (OOP), Procedural Programming, Security-Oriented Programming (SOP), and Structured Programming. Ada stands out in the programming world due to its strong typing, modularity, and exceptional error-checking capabilities. Designed for reliability and efficiency, Ada is the go-to language for critical systems where safety and security are paramount. This book delves into these essential features, providing a solid foundation for developing reliable and maintainable software systems. Learn about Ada’s powerful type system, modular programming capabilities, and robust error-handling mechanisms, all of which are crucial for creating software that is both reliable and maintainable. The journey begins with an introduction to the basic constructs of Ada, providing readers with a solid foundation in the language's syntax and semantics. We explore fundamental concepts such as data types, control structures, and subprograms, emphasizing Ada’s strict type checking and error prevention mechanisms. Through clear explanations and practical examples, readers will gain confidence in writing correct and efficient Ada code from the outset. Building on this foundation, the book transitions into more advanced topics, including object-oriented programming, generic programming, and tasking. These chapters highlight Ada’s unique approach to these paradigms, demonstrating how its features can be used to create modular, reusable, and concurrent systems. By understanding these advanced concepts, readers will be equipped to tackle complex software challenges with Ada’s robust toolkit.

Название: Artificial Intelligence: A Guide for Everyone
Автор: Arshad Khan
Издательство: Springer
Год: 2024
Страниц: 278
Язык: английский
Формат: pdf (true), epub
Размер: 10.1 MB

Enterprises, as well as individuals, are racing to reap the benefits of Artificial Intelligence (AI). However, in most cases, they are doing so without understanding the technology or its implications and risks, which can be significant. Artificial Intelligence: A Guide for Everyone is a step in addressing that gap by providing information that readers can easily understand at every level. This book aims to provide useful information to those planning, developing, or using AI, which has the potential to transform industries and shape the future. Artificial Intelligence: A Guide for Everyone encompasses theoretical as well as practical aspects of AI across various industries and applications. It demystifies AI by explaining, in a language that non-techies can follow, its history, different types, differentiating technologies, and various aspects of implementation. It explains the connection between AI theory and real-world application across diverse industries and how it fuels innovation. Whether you are a simple business user, a professional, a tech enthusiast, a manager, an executive, or an aspiring AI developer, this guide is your roadmap to navigate the intricacies of AI. The topics covered in this book are comprehensive and diverse. This guide explains the prerequisites for building, developing, and deploying an AI system. It discusses its key techniques, technologies, and components, such as Machine Learning, natural language processing, and Deep Learning. It explains the process of constructing an AI system, offering insights into problem definition, data preprocessing, model development, evaluation, testing, deployment, and monitoring. In consideration of practical resource limitations and constraints, pre-built, ready-to-use AI solutions, which democratize AI, are discussed. The journey concludes by categorizing AI based on intelligence levels and functionality, providing a comprehensive understanding of Artificial Narrow Intelligence (ANI), Artificial General Intelligence (AGI), Artificial Super Intelligence (ASI), and other categories.

Название: Geophysical Data Analysis and Inverse Theory with MATLAB and Python, 5th Edition
Автор: William Menke
Издательство: Academic Press, Elsevier
Год: 2024
Страниц: 344
Язык: английский
Формат: pdf (true)
Размер: 29.7 MB

Geophysical Data Analysis and Inverse Theory with MATLAB or Python, Fifth Edition is a revised and expanded introduction to inverse theory and tomography as it is practiced by geophysicists. The book demonstrates the methods needed to analyze a broad spectrum of geophysical datasets, with special attention given to those methods that generate images of the earth. Data analysis can be a mathematically complex activity, but the treatment in this volume is carefully designed to emphasize those mathematical techniques that readers will find the most familiar and to systematically introduce less-familiar ones. A series of "crib sheets" offer step-by-step summaries of methods presented. Utilizing problems and case studies, along with MATLAB and Python computer code and summaries of methods, the book provides professional geophysicists, students, data scientists and engineers in geophysics with the tools necessary to understand and apply mathematical techniques and inverse theory. MATLAB and Python scripts are used throughout the book as a means of communicating how the formulas of inverse theory can be used in computer-based data processing scenarios. MATLAB is a commercial software product of The MathWorks, Inc. Python and its many add-ons, such as the NumPy linear algebra package, the SciPy scientific function package, and the Jupyter Notebook/JupyterLab environment, are freeware that offer an alternative to MATLAB and other commercial products with license fees. Both are widely used in university settings as an environment for scientific computing.

Название: Collaborative Filtering: Recommender Systems
Автор: Angshul Majumdar
Издательство: CRC Press
Год: 2025
Страниц: 142
Язык: английский
Формат: pdf (true)
Размер: 14.2 MB

This book dives into the inner workings of recommender systems, those ubiquitous technologies that shape our online experiences. From Netflix show suggestions to personalized product recommendations on Amazon or the endless stream of curated YouTube videos, these systems power the choices we see every day. Collaborative filtering reigns supreme as the dominant approach behind recommender systems. This book offers a comprehensive exploration of this topic, starting with memory-based techniques. These methods, known for their ease of understanding and implementation, provide a solid foundation for understanding collaborative filtering. As you progress, you’ll delve into latent factor models, the abstract and mathematical engines driving modern recommender systems. The journey continues with exploring the concepts of metadata and diversity. You’ll discover how metadata, the additional information gathered by the system, can be harnessed to refine recommendations. Additionally, the book delves into techniques for promoting diversity, ensuring a well-balanced selection of recommendations. Finally, the book concludes with a discussion of cutting-edge Deep Learning models used in recommender systems. Recommender systems, powered by sophisticated algorithms and Machine Learning techniques, analyze user behavior, preferences, and past consumption patterns to identify patterns and predict future choices. These systems act as digital surrogates for the trusted friends, family, and experts who traditionally guided consumer decisions in the pre-internet era. The book assumes a basic understanding of linear algebra and optimization but requires no prior knowledge of Machine Learning or programming.

Название: Introducing Microsoft Copilot for Managers: Enhance Your Team's Productivity and Creativity with Generative AI-Powered Assistant
Автор: Adeel Khan
Издательство: Apress
Год: 2024
Страниц: 696
Язык: английский
Формат: pdf
Размер: 32.1 MB

Embark on an exhilarating journey through the digital landscape with Microsoft Copilots, a suite of AI-powered tools that help you create, edit, and optimize content, code, and data across various Microsoft platforms. This book will be your indispensable guide to harnessing the power of generative AI within the Microsoft ecosystem, introducing you to various copilots and their impact on your business processes. The book will guide you as a manager to leverage Microsoft Copilot to improve your personal productivity, your team's productivity, and achieve your business goals with success. This book is organized into five parts. The first part introduces you to Microsoft Copilot and its features and benefits. In the second part, you will get an overview of the integration of Microsoft Copilot with M365 tools. The third part teaches you about the maker copilot in Power Platform services followed by the business expert copilot for Sales and Service for Business Applications such as Dynamics 365 and Salesforce. The book also introduces you to Copilot Studio to help you extend the copilots or build your own. By the end of this book, you will have a solid understanding of Microsoft Copilot and how to use copilots effectively and efficiently with various transformation platforms. You will also have a collection of tips, tricks, and best practices to help you get the most out of Microsoft Copilot. Microsoft Copilot uses a type of Machine Learning model known as a large language model (LLM).

Название: Large Language Model-Based Solutions: How to Deliver Value with Cost-Effective Generative AI Applications
Автор: Shreyas Subramanian
Издательство: Wiley
Год: 2024
Страниц: 221
Язык: английский
Формат: pdf (true), epub (true)
Размер: 10.6 MB, 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: Gesture Recognition: Theory and Applications
Автор: Qiguang Miao, Yunan Li, Xiangzeng Liu, Ruyi Liu
Издательство: Elsevier
Год: 2024
Страниц: 200
Язык: английский
Формат: epub (true)
Размер: 10.1 MB

Gesture Recognition: Theory and Applications covers this important topic in Computer Science and language technology that has a goal of interpreting human gestures via mathematical algorithms. The book begins by examining the computer vision-based gesture recognition method, focusing on the theory and related research results of various recent gesture recognition technologies. The book takes the evolutions of gesture recognition technology as a clue, systematically introducing gesture recognition methods based on handcrafted features, convolutional neural networks, recurrent neural networks, multimodal data fusion, and visual attention mechanisms. Three gesture recognition-based HCI (Human Computer Interaction) practical cases are introduced. Finally, the book looks at emerging research trends and application. Focuses on the theory and application of gesture recognition, providing a systematic introduction to commonly used datasets in the field as well as algorithms based on handcrafted features, convolutional neural networks, multimodal fusion, and attention mechanisms. Introduces the practical applications of gesture recognition in real-world scenarios, enabling readers to enhance their practical application skills while learning about relevant technologies. Demonstrates four main categories of gesture recognition methods and analyzes their associated challenges.

Название: Federated Deep Learning for Healthcare: A Practical Guide with Challenges and Opportunities
Автор: Amandeep Kaur, Chetna Kaushal, Md. Mehedi Hassan, Si Thu Aung
Издательство: CRC Press
Год: 2025
Страниц: 267
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

This book provides a practical guide to Federated Deep Learning for healthcare including fundamental concepts, framework, and the applications comprising of domain adaptation, model distillation, and transfer learning. It covers concerns in model fairness, data bias, regulatory compliance, and ethical dilemmas. It investigates several privacy-preserving methods like homomorphic encryption, secure multi-party computation, and differential privacy. It will enable readers to build and implement Federated Learning systems that safeguard private medical information. This book is aimed at graduate students and researchers in Federated Learning, Data Science, AI/Machine Learning, and healthcare.

Название: Code the Classics Volume I, 2nd Edition
Автор: Russell Barnes
Издательство: Raspberry Pi Press
Год: 2024
Страниц: 240
Язык: английский
Формат: epub (true)
Размер: 46.4 MB

Take inspiration from the golden age of video games and learn how to write your own modern classics. Code the Classics Volume 1 not only tells the stories of some of the seminal video games of the 1970s and 1980s, but shows you how to create your own games inspired by them, following examples programmed by Raspberry Pi founder Eben Upton. In this book, you'll learn how to run and edit the games in this book by installing Python, Pygame Zero, and an IDE. You'll also: - Get game design tips and tricks from the masters; - Learn how to code your own games with Pygame Zero; - Explore the code listings and find out how they work.

Название: Evasive Malware: A Field Guide to Detecting, Analyzing, and Defeating Advanced Threats
Автор: Kyle Cucci
Издательство: No Starch Press
Год: 2024
Страниц: 490
Язык: английский
Формат: True/Retail (PDF EPUB)
Размер: 58.8 MB

Get up to speed on state-of-the-art malware with this first-ever guide to analyzing malicious Windows software designed to actively avoid detection and forensic tools. We’re all aware of Stuxnet, ShadowHammer, Sunburst, and similar attacks that use evasion to remain hidden while defending themselves from detection and analysis. Because advanced threats like these can adapt and, in some cases, self-destruct to evade detection, even the most seasoned investigators can use a little help with analysis now and then. Evasive Malware will introduce you to the evasion techniques used by today’s malicious software and show you how to defeat them. Following a crash course on using static and dynamic code analysis to uncover malware’s true intentions, you’ll learn how malware weaponizes context awareness to detect and skirt virtual machines and sandboxes, plus the various tricks it uses to thwart analysis tools. You’ll explore the world of anti-reversing, from anti-disassembly methods and debugging interference to covert code execution and misdirection tactics. You’ll also delve into defense evasion, from process injection and rootkits to fileless malware. Finally, you’ll dissect encoding, encryption, and the complexities of malware obfuscators and packers to uncover the evil within.