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Gesamtkatalog

Catalogue complet

Kingsford C: An Introduction to String
Algorithms

An Introduction to String Algorithms

Artificial Intelligence and Machine Learning for Safety-Critical Systems: A Comprehensive Guide provides engineers and system designers who are exploring the application of AI/ML methods for safety-critical systems with a dedicated resource capturing the challenges and mitigation strategies involved in designing such systems. Divided into nine sections, the book covers the most important applications of safety-critical systems, helping readers understand how related problems are being solved in different domains/problem settings. The goal of this book is to help ensure that AI-based critical systems better utilize resources, avoid failures, and increase system safety and public safety. The authors present ML techniques in safety-critical systems across multiple domains, including pattern recognition, image processing, edge computing, Internet of Things (IoT), encryption, hardware accelerators, and many others. These applications help readers understand the many challenges that need to be addressed in order to increase the deployment of ML models in critical systems. In addition, the book shows how to improve public trust in ML systems by providing explainable model outputs rather than treating the system as a black box for which the outputs are difficult to explain. Finally, the authors demonstrate how to meet legal certification and regulatory requirements for the appropriate ML models.

A Comprehensive Guide

Artificial Intelligence and Machine Learning for Safety-Critical Systems

A Four Billion Year Conversation

Earth and Life

Foundations of Biochemistry and Biophysics

The Compressible Fluid Physics of the Human Respiratory System provides a comprehensive exploration of the principles of fluid dynamics, classical mechanics, and their applications to complex systems such as human respiration.It dives into foundational concepts like Newtonian mechanics and stress-strain relationships, while also addressing advanced topics such as compressible fluid flow, viscosity, and energy conservation. It uniquely combines classical principles with real-world phenomena, such as the behavior of gases, liquids, and solids under various forces and pressures. The inclusion of detailed mathematical derivations, historical context, and empirical models adds depth to the discussion. Its interdisciplinary approach makes it valuable for readers interested in physics, engineering, and biological sciences.This book is designed for a general audience with an interest in science and medicine irrespective of mathematical background.

The Compressible Fluid Physics of the Human Respiratory System

Distributed and Parallel Computing

Forensic Engineering for Academia

Methods, Applications, and Implications

Adaptive AI in Sensor Informatics

This book is a comprehensive guide that immerses you into the world of building and deploying AI-powered solutions. You are introduced to the core architecture of LLMs and equipped with essential Best Data Practices (BDPs) for utilizing Generative AI responsibly, ensuring ethical and efficient AI deployment.The book starts with the foundational aspects of Generative AI application development. You will learn the nuances of data handling in Generative AI apps, from working with embeddings to managing unstructured and structured data, and handling Personally Identifiable Information (PII) data. The exploration extends to understanding the differences between deterministic and LLM-based data synthesis and integrating Generative AI apps with enterprise data, providing you with practical insights into leveraging data effectively for intelligent applications. A chapter on prompt engineering explains the importance of prompts in AI interactions, covering a spectrum of techniques and pitfalls while offering exercises to enhance prompt engineering skills. As you progress through the book, you take a journey from conceptualization to production and deployment of Generative AI applications. You discover the essentials of Generative AI application development, gain insights into the pathway from ideation to production, and explore the intricacies of LLM selection and fine-tuning.The book equips you with the knowledge and tools necessary to navigate the complex terrain of AI development and deployment, making it an indispensable resource for AI enthusiasts, developers, and business leaders alike.What You Will Learn<ul><li>Know the core architecture of LLMs and how these models have revolutionized AI applications</li><li>Handle various data types, including unstructured, structured, and personally identifiable information (PII) data in Generative AI applications</li><li>Understand prompt engineering and its importance in AI interactions and applications</li><li>Understand modular design of Generative AI apps, essential backend and frontend components, and the unique principles guiding Generative AI app design</li></ul>&nbsp;&nbsp;

This book is a comprehensive guide that immerses you into the world of building and deploying AI-powered solutions. You are introduced to the core architecture of LLMs and equipped with essential Best Data Practices (BDPs) for utilizing Generative AI responsibly, ensuring ethical and efficient AI deployment.The book starts with the foundational aspects of Gehatnerative AI application development. You will learn the nuances of data handling in Generative AI apps, from working with embeddings to managing unstructured and structured data, and handling Personally Identifiable Information (PII) data. The exploration extends to understanding the differences between deterministic and LLM-based data synthesis and integrating Generative AI apps with enterprise data, providing you with practical insights into leveraging data effectively for intelligent applications. A chapter on prompt engineering explains the importance of prompts in AI interactions, covering a spectrum of techniques and pitfalls while offering exercises to enhance prompt engineering skills. As you progress through the book, you take a journey from conceptualization to production and deployment of Generative AI applications. You discover the essentials of Generative AI application development, gain insights into the pathway from ideation to production, and explore the intricacies of LLM selection and fine-tuning.The book equips you with the knowledge and tools necessary to navigate the complex terrain of AI development and deployment, making it an indispensable resource for AI enthusiasts, developers, and business leaders alike.&nbsp;What You Will Learn<ul><li>Know the core architecture of LLMs and how these models have revolutionized AI applications</li><li>Handle various data types, including unstructured, structured, and personally identifiable information (PII) data in Generative AI applications</li><li>Understand prompt engineering and its importance in AI interactions and applications</li><li>Understand modular design of Generative AI apps, essential backend and frontend components, and the unique principles guiding Generative AI app design</li></ul>&nbsp;Who This Book Is ForFrom AI enthusiasts exploring the field to software developers seeking practical insights, and business leaders looking to harness the power of AI for organizational growth and innovation&nbsp;&nbsp;

Building and Deploying Ethical AI-Powered Solutions

Practical Generative AI: From Concept to Deployment

Theoretical and Computational Chemistry

Methods and Applications

Introduction to Computational Chemistry

Powered by Hyperscale Computing and Next Generation Networks

AI-Driven Smart Healthcare

Targeting DNA Repair Mechanisms, Tumor Genetics, and Signaling Pathways: Synergistic Approaches in Gastrointestinal Cancer Treatment provides a comprehensive exploration of the complex mechanisms underlying gastrointestinal (GI) cancers, including colorectal, gastric, liver, and pancreatic malignancies. This book addresses the urgent need for innovative therapeutic strategies by synthesizing current research on DNA repair, tumor genetics, and cellular signaling pathways critical to cancer progression and treatment. The content examines the roles of DNA repair mechanisms and the influence of genetic factors on personalized medicine, while also discussing the potential of combining targeted therapies to enhance treatment efficacy. Featuring real-world case studies and insights from leading experts, the book bridges the gap between basic research and clinical application. For the academic audience, this resource promotes a holistic understanding of GI cancer biology, addresses treatment resistance, and fosters collaboration among researchers and clinicians, ultimately improving patient outcomes in this rapidly evolving field.

An Introduction to String Algorithms

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