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  • Sách/Book

  • Computer security: principles and practice

    • Authors: William Stallings (2018)

  • The objective of this book is to provide an up-to-date survey of developments in computer security. Central problems that confront security designers and security administrators include defining the threats to computer and network systems, evaluating the relative risks of these threats, and developing cost-effective and user friendly countermeasures
  • Sách/Book

  • Explainable Artificial Intelligence: An Introduction to Interpretable Machine Learning

    • Authors: Uday Kamath (2021)

  • This book takes an in-depth approach to presenting the fundamentals of explain-able AI through mathematical theory and practical use cases. The content is split into four parts: pre-model methods, intrinsic methods, post-hoc methods, and deep- learning methods. The first part introduces pre-model techniques for Explainable AI (XAI). Part Two presents classical and modern intrinsic model interpretability methods, while Part Three details the collection of post-hoc methods. Part Four dives into methods tailored specifically for deep learning models.
  • Sách/Book

  • Explainable AI: Foundations, Methodologies and Applications

    • Authors: Mayuri Mehta (2023)

  • This book presents an overview and several applications of explainable artificial intelligence (XAI). It covers different aspects related to explainable artificial intelligence, such as the need to make the AI models interpretable, how black box machine/deep learning models can be understood using various XAI methods, different evaluation metrics for XAI, human-centered explainable AI, and applications of explainable AI in health care, security surveillance, transportation, among other areas.
  • Sách/Book

  • Generative AI For Dummies

    • Authors: Pam Baker (2025)

  • Generative AI tools capable of creating text, images, and even ideas seemingly out of thin air have exploded in popularity and sophistication. This valuable technology can assist in authoring short and long-form content, producing audio and video, serving as a research assistant, and tons of other professional and personal tasks. Generative AI For Dummies is your roadmap to using the world of artificial intelligence to enhance your personal and professional lives. You'll learn how to identify the best platforms for your needs and write the prompts that coax out the content you want. Written by the best-selling author of ChatGPT For Dummies, this book is the ideal place to start when you're ready to fully dive into the world of generative AI.
  • Sách/Book

  • The Art of Network Architecture: Business-Driven Design

    • Authors: Russ White (2014)

  • The Art of Network Architecture is the first book that places business needs and capabilities at the center of the process of architecting and evolving networks. Two leading enterprise network architects help you craft solutions that are fully aligned with business strategy, smoothly accommodate change, and maximize future flexibility.Russ White and Denise Donohue guide network designers in asking and answering the crucial questions that lead to elegant, high-value solutions. Carefully blending business and technical concerns, they show how to optimize all network interactions involving flow, time, and people.
  • Sách/Book

  • Enterprise systems for management

    • Authors: Luvai F. Motiwalla (2012)

  • This edition specifically:• provides several examples of real-world company issues that occurred while implementing enterprise systems;• provides a step-by-step learning process for students, using organized materials, and learning • focuses on a pedagogy that lays out concise learning goals and reinforces the concepts learned using cases, discussion questions, and exercises; andabout enterprise system implementations;• highlights issues within the implementation process that have implications for management.
  • Sách/Book

  • Fundamentals of Reinforcement Learning

    • Authors: Rafael Ris-Ala (2023)

  • This book provides an introduction to AI, specifies machine learning techniques, and explores various aspects of reinforcement learning, approaching the latest concepts in a didactic and illustrated manner. It is aimed at students who want to be part of technological advances and professors engaged in the development of innovative applications, helping with academic and industrial challenges
  • Sách/Book

  • Fundamentals of Pattern Recognition and Machine Learning

    • Authors: Ulisses Braga-Neto (2021)

  • This book is a concise but thorough introduction to the tools commonly used in pattern recognition and machine learning, including classification, dimensionality reduction, regression, and clustering, as well as recent popular topics such as deep neural networks and Gaussian process regression. The Second Edition is thoroughly revised, featuring a new chapter on the emerging topic of physics-informed machine learning and additional material on deep neural networks.
  • Sách/Book

  • Exploring Windows Presentation Foundation: With Practical Applications in .NET 5

    • Authors: Taurius Litvinavicius (2021)

  • This book will get you through not only the basics, but also some of the more advanced concepts of WPF in .NET 5.The book starts with basic concepts such as window, page, text box, and message box as well as a sequence of common events and event handling in WPF. You will learn how to use various elements in WPF and deal with them in .NET 5. You will understand how to work with files and access them in WPF along with binding and MVVM (Model-View-View-Model). You will learn how to retrieve data from APIs, work in XAML, and understand where design and style properties should be applied in WPF.