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Commentaires

Marcella Albert J.: Auditing Artificial
Intelligence

Auditing Artificial Intelligence

A Handbook for Audit, Risk, and Security Professionals

Psychophysics and Experimental Phenomenology of Pattern Cognition

Beck international

The Book
Artificial Intelligence will profoundly shape the future economy and society. Whereas the potential benefits are notable and desirable, the risk of serious harm is considerable. The new EU AI Act 2024/1689 therefore seeks to provide a legal framework to regulate AI systems in the EU.
Written by an international team of experts, this Article-by-Article Commentary provides a comprehensive analysis and explanation of each of the provisions of the AI Act to assist in the interpretation and application. Each commentary follows a clear and uniform structure, also providing key information on the function and context of each provision. Where appropriate, practice tips are also given.

The Advantages at a GlanceComprehensive analysisInternational team of renowned expertsClear and uniform structure
The Target Group
For in-house counsel, legal practitioners, scholars, supervisory authorities, industry groups.

The Book
Artificial Intelligence will profoundly shape the future economy and society. Whereas the potential benefits are notable and desirable, the risk of serious harm is considerable. The new EU AI Act 2024/1689 therefore seeks to provide a legal framework to regulate AI systems in the EU.
Written by an international team of experts, this Article-by-Article Commentary provides a comprehensive analysis and explanation of each of the provisions of the AI Act to assist in the interpretation and application. Each commentary follows a clear and uniform structure, also providing key information on the function and context of each provision. Where appropriate, practice tips are also given.

The Advantages at a GlanceComprehensive analysisInternational team of renowned expertsClear and uniform structure
The Target Group
For in-house counsel, legal practitioners, scholars, supervisory authorities, industry groups.

Article-by-Article Commentary

Artificial Intelligence Act

Building and Deploying AI Applications at Scale

ML and Generative AI in the Data Lakehouse

Sustainable Computing and Optimization

Trends and Future Challenges

Managing Sustainable Operations of Logistics and Supply Chain Management

You've experienced the shiny, point-and-click surface of your Linux computer—now dive below and explore its depths with the power of the command line. The Linux Command Line takes you from your very first terminal keystrokes to writing full programs in Bash, the most popular Linux shell (or command line). Along the way you'll learn the timeless skills handed down by generations of experienced, mouse-shunning gurus: file navigation, environment configuration, command chaining, pattern matching with regular expressions, and more. In addition to that practical knowledge, author William Shotts reveals the philosophy behind these tools and the rich heritage that your desktop Linux machine has inherited from Unix supercomputers of yore. As you make your way through the book's short, easily-digestible chapters, you'll learn how to: <ul><li>Create and delete files, directories, and symlinks</li><li>Administer your system, including networking, package installation, and process management</li><li>Use standard input and output, redirection, and pipelines</li><li>Edit files with Vi, the world's most popular text editor</li><li>Write shell scripts to automate common or boring tasks</li><li>Slice and dice text files with cut, paste, grep, patch, and sed</li></ul> Once you overcome your initial "shell shock," you'll find that the command line is a natural and expressive way to communicate with your computer. Just don't be surprised if your mouse starts to gather dust.

A Complete Introduction

The Linux Command Line, 3rd Edition

The Deep Learning Revolution

Cybersecurity Threat Mitigation Lessons from a Real-World Lockbit Ransomware Response

Locked Up

Synthesis Lectures on Technology and Health

<div>This book provides a comprehensive overview of palliative care digital health by covering current developments, methodology, clinical relevance, research priorities, ethical issues, and policy related to technological innovations for those with serious illness. This type of book does not currently exist in the literature, as previous work primarily focuses on digital health for early identification of disease and facilitating self-care or ‘aging in place’ practices. This book addresses the lack of focus on digital health for people with palliative care needs. This book has a special focus on the needs of individuals as their health worsens throughout their illness. Consequently, the reader will benefit from this book’s focus on the science, methodology, application, and practicality of digital health developments in palliative care.</div>
<div>This book explores the barriers that prevent the meaningful use of digital health in palliative care, including expenses, interoperability issues, data privacy and security concerns, lack of effectiveness and equity, and the concern that technology may reduce face-to-face consultations between patients and clinicians. There is an overall lack of consensus about digital health research priorities in palliative care, and a lack of theories about how these technologies might improve care outcomes. Therefore, this book emphasizes the importance of identifying, discussing, and debating how technological innovations can be meaningfully used to ensure that frail people have appropriate access to palliative care services. Consequently, this book begins the conversation about articulating digital health research priorities in palliative care to determine how finite resources should be allocated to a field saturated with rapidly developing innovation.</div>

Technologies in Palliative Care for Older People

Progress In Data Science

Ubiquitous Laplacian: An Introduction To Numerical Pdes With Applications In Data Science

Retrieval-Augmented Generation (RAG) represents the cutting edge of AI innovation, bridging the gap between large language models (LLMs) and real-world knowledge. This book provides the definitive roadmap for building, optimizing, and deploying enterprise-grade RAG systems that deliver measurable business value.
This comprehensive guide takes you beyond basic concepts to advanced implementation strategies, covering everything from architectural patterns to production deployment. You'll explore proven techniques for document processing, vector optimization, retrieval enhancement, and system scaling, supported by real-world case studies from leading organizations.
Key Learning Objectives
<ul>
<li>Design and implement production-ready RAG architectures for diverse enterprise use cases</li>
<li>Master advanced retrieval strategies including graph-based approaches and agentic systems</li>
<li>Optimize performance through sophisticated chunking, embedding, and vector database techniques</li>
<li>Navigate the integration of RAG with modern LLMs and generative AI frameworks</li>
<li>Implement robust evaluation frameworks and quality assurance processes</li>
<li>Deploy scalable solutions with proper security, privacy, and governance controls</li>
</ul>
Real-World Applications
<ul>
<li>Intelligent document analysis and knowledge extraction</li>
<li>Code generation and technical documentation systems</li>
<li>Customer support automation and decision support tools</li>
<li>Regulatory compliance and risk management solutions</li>
</ul>
Whether you're an AI engineer scaling existing systems or a technical leader planning next-generation capabilities, this book provides the expertise needed to succeed in the rapidly evolving landscape of enterprise AI.
What You Will Learn
<ul>
<li>Architecture Mastery: Design scalable RAG systems from prototype to enterprise production</li>
<li>Advanced Retrieval: Implement sophisticated strategies, including graph-based and multi-modal approaches</li>
<li>Performance Optimization: Fine-tune embedding models, vector databases, and retrieval algorithms for maximum efficiency</li>
<li>LLM Integration: Seamlessly combine RAG with state-of-the-art language models and generative AI frameworks</li>
<li>Production Excellence: Deploy robust systems with monitoring, evaluation, and continuous improvement processes</li>
<li>Industry Applications: Apply RAG solutions across diverse sectors, including finance, healthcare, legal, and technology</li>
</ul>

Advanced Techniques and Production-Ready Solutions for Enterprise AI

Mastering Retrieval-Augmented Generation

Expert reference on building surrogate models, optimization using them, prediction uncertainty associate with them, and their potential failure, with practical implementation in MATLAB Surrogate Modeling and Optimization explains the meaning of different surrogate models and provides an in-depth understanding of such surrogates, emphasizing how much uncertainty is associated with them, and when and how a surrogate model can fail in approximating complex functions and helping readers understand theory through practical implementation in MATLAB. This book enables readers to obtain an accurate approximate function using as few samples as possible, thereby allowing them to replace expensive computer simulations and experiments during design optimization, sensitivity analysis, and/or uncertainty quantification. The book is organized into three parts. Part I introduces the basics of surrogate modeling. Part II reviews various theories and algorithms of design optimization. Part III presents advanced topics in surrogate modeling, including the Kriging surrogate, neural network models, multi-fidelity surrogates, and efficient global optimization using Kriging surrogates. The book is divided into 10 chapters. Each chapter contains about 10 examples and 20 exercise problems. Lecture slides and a solution manual for exercise problems are available for instructors on a companion website. Sample topics discussed in Surrogate Modeling and Optimization include: <ul> <li>Various designs of experiments, such as those developed for linear and quadratic polynomial response surfaces (PRS) in a boxlike design space</li> <li>Criteria for constrained and unconstrained optimization and the most important optimization theories</li> <li>Various numerical algorithms for gradient-based optimization</li> <li>Gradient-free optimization algorithms, often referred to as global search algorithms, which do not require gradient or Hessian information</li> <li>Detailed explanations and implementation on Kriging surrogate, often referred to as Gaussian Process, especially when samples include noise</li> <li>The combination of a small number of high-fidelity samples with many low-fidelity samples to improve prediction accuracy</li> <li>Neural network models, focusing on training uncertainty and its effect on prediction uncertainty</li> <li>Efficient global optimization using either polynomial response surfaces or Kriging surrofates</li> </ul> Surrogate Modeling and Optimization is an essential learning companion for senior-level undergraduate and graduate students in all engineering disciplines, including mechanical, aerospace, civil, biomedical, and electrical engineering. The book is also valuable for industrial practitioners who apply the surrogate model to solve their optimization problems.

Theories, Applications, and Limitations

Surrogate Modeling and Optimization

Sybex Study Guide

The fastest and most effective way to learn the fundamentals of Azure cloud technology and prepare for the AZ-900 certification exam The newly updated second edition of Microsoft Certified Azure Fundamentals Study Guide is an accurate and up-to-date roadmap to the AZ-900 certification exam and a reliable, effective resource for everyone seeking to learn about or reinforce their knowledge of Azure services, pricing, security and compliance, resource management, and more. In the book, experienced Microsoft Principal Customer Success Account Manager and long-time author, Jim Boyce, covers every foundational Azure competency, including: <ul> <li>General and foundational cloud concepts</li> <li>Azure Core Services, including architecture, subscription and billing options, data services, and virtual machines</li> <li>Azure Core Networking Services, like virtual networks, load balancers, and VPN gateways</li> <li>Security, compliance, privacy, and trust features</li> <li>Azure Solutions, like AI and machine learning, serverless computing, and IoT</li> <li>Azure pricing, service levels, and lifecycles</li> <li>Azure Resource creation and management</li> </ul> Ideal for technical and non-technical professionals alike, this straightforward Study Guide draws on the proven Sybex model to explain core Azure features and concepts. It will get you ready to succeed on the widely used AZ-900 certification test and elevate your understanding of Azure cloud software, improving your day-to-day performance in any role that directly or indirectly intersects with the cloud platform. Inside the book <ul> <li>End-of-chapter review questions, with answers and explanations, you can use to measure your progress and help you focus on the areas where you need to improve</li> <li>Concise and intuitive explanations of core Azure services, functions, and features</li> <li>Complimentary access to the superior Sybex online learning environment and test bank, including practice test questions, digital flashcards, and a glossary of key terms</li> </ul> With authoritative, concise coverage of all relevant cloud concepts, Azure architecture and services, and management and governance features tested by the AZ-900 certification exam, this edition of Microsoft Certified Azure Fundamentals Study Guide is the fastest, most efficient way to get up to speed on foundational Azure cloud competencies.

Exam AZ-900

MC Azure Fundamentals Study Guide

Auditing Artificial Intelligence

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