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Gesamtkatalog

Catalogue complet

Applications of Federated Learning in
Technological Advancements

Applications of Federated Learning in Technological Advancements

Use Cases and Applications

Augmented and Virtual Reality in Healthcare

Artificial Intelligence and Machine Learning in Data Science and Analytics

This unique compendium presents the basics of the theory of computing at a level and in a manner that can be easily understood by computer science students in a large university. It offers the student a firm foundation in logical reasoning and covers many traditional topics in unconventional ways.The useful reference text benefits professionals, academics, researchers and undergraduate students in the area of theoretical computer science.

Foundation Of Computation: Languages And Machines

A Path to Sustainable Development Goals

AI and ML Techniques in IoT-based Communication

Combining Human Thinking and Creativity with Technology to Inspire Audiences

Authentic Marketing

FinTech and the Remaking of Financial Institutions, Second Edition explores the transformative potential of new entrants and innovations on business models. In its survey and analysis of FinTech, the book addresses current and future states of money and banking. It provides broad contexts for understanding financial services, products, technology, regulations, and social considerations. The Second Edition expands and updates topics covered in the first edition, with particular emphasis on current and expected impact of AI; maturation of crypto and consequent regulatory issues; international developments; and the continued integration of technology advances in large financial institutions. The book shows how FinTech has evolved and will drive the future of financial services. It sheds new light on disruption, innovation and opportunity by placing the financial technology revolution in larger contexts. After an introductory chapter, chapters 2-12 present a necessary background of economics and finance as well as selected Fintech companies that are active in specific markets. Chapters 13-17 then broaden the scope to discuss the financing of startups; FinTech activity in hubs outside of the United States; financial regulation; negative impacts of FinTech on some social issues; and finally, responses of the Big Financial Institutions to the FinTech disruption. FinTech and the Remaking of Financial Institutions, Second Edition is a valuable resource for students, researchers, and professionals alike who need to understand the latest emerging FinTech technologies, how they’re used in finance, how they are regulated, and the societal implications.

Fintech and the Remaking of Financial Institutions

An expert compilation of on-device training techniques, regulatory frameworks, and ethical considerations of TinyML design and development In Tiny Machine Learning: Design Principles and Applications, a team of distinguished researchers delivers a comprehensive discussion of the critical concepts, design principles, applications, and relevant issues in Tiny Machine Learning (TinyML). Expert contributors introduce a new low power resource, offering vast applications in IoT devices with system-algorithm co-design. Tiny Machine Learning explores TinyML paradigms and enablers, TinyML for anomaly detection, and the learning panorama under TinyML. Readers will find explanations of TinyML devices and tools, power consumption and memory in IoT microcontrollers, and lightweight frameworks for TinyML. The book also describes TinyML techniques for real-time and environmental applications. Additional topics covered in the book include: <ul> <li>A thorough introduction to security and privacy techniques for TinyML devices, including the implementation of novel security schemes</li> <li>Incisive explorations of power consumption and memory in IoT MCUs, including ultralow-power smart IoT devices with embedded TinyML</li> <li>Practical discussions of TinyML research targeting microcontrollers for data extraction and synthesis</li> </ul> Perfect for industry and academic researchers, scientists, and engineers, Tiny Machine Learning will also benefit lecturers and graduate students interested in machine learning.

Tiny Machine Learning: Design Principles and Applications

Readings in Theatre Practice

Keywords and Concepts

Acting

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;

Building and Deploying Ethical AI-Powered Solutions

Practical Generative AI: From Concept to Deployment

Enhancing Reflective Teaching in Higher Education

Redefining Teaching and Learning

GenAI in Higher Education

Advances in Industrial and Systems Engineering

Advances in Human-AI Collaboration

Intelligent IoT-based Diagnostic and Assistive Systems for Neurological Disorders

Applications of Federated Learning in Technological Advancements

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