<div class="raw-html-embed"> Newsletteraktion: Abonnieren Sie jetzt unseren Newsletter und sichern Sie sich bis zum 8. August 2025 10% Rabatt auf Ihre Onlinebestellungen. <a href="/newsletter">Infos und Anmeldung.</a></div>

NL_Doormat: Hintergrundfarbe des Newsletter Banners unten in der Doormat. Mit # eingeben z.B. #1405BE

NL_Doormat: Verlinkung zur Newsletter Seite

Über uns

À propos de nous

Zahlung und Lieferung

Paiement et livraison

Nachhaltigkeit

Durabilité

Open Access

Datenschutz

Protection des données

Karriere

Carrière

Impressum

Mentions légales

LEXIA

LEXIA Arbeitsrecht

Was ist LEXIA?

C'est quoi LEXIA ?

LEXIA Familienrecht

Zeitschriften

Revues

recht

Pflegerecht

ZBJV

forumpoenale

ZStrR

Anwaltsrevue

Revue de l'avocat

RSAS

FamPra.ch

ASYL

Life Science Recht

BlAR

Sachbuch

Livres spécialisés

LOKI

Semaphor

Fokusthemen

Focus

Thema

Recht studieren

Arbeitsrecht

Droit du travail

Studium

Études

Familienrecht

Droit de la famille

Sozialversicherungsrecht

Droit des assurances sociales

Strafrecht

Droit pénal

Publikationen

Publications

Literatur

Onlinemodule LEXIA

Modules en ligne LEXIA

Bücher

Livres

Buchreihen

Collections

Datenbanken

recht.ch

Studienliteratur

Littérature pour les études

Services

Dienstleistungen für

Corporate Books

Publishing Lösungen

Aktuelles

Geschäftskunden

Professionnels

Corporate Publishing

Content solutions

Buchhandlungen

Librairies

Veranstaltungen

Événements

Presse

Dozierende

Enseignants

Studierende

Étudiants

Inserierende

Annonceurs

Newsletter

Blog

Autorinnen/Autoren

Auteurs

Unsere Schreibenden

Hilfe

Unsere Autorinnen und Autoren

Liste

Autorenlounge

Espace des auteurs

Bei uns publizieren

Publier chez nous

Autorenstimmen

Témoignages

Verlag

Éditions

Themen

Mehr wissen

Mitarbeitende

Collaborateurs

Geschichte

Histoire

Vision und Mission

Vision et mission

Unser Magazin

Notre magazine

Unternehmenskultur

Culture d'entreprise

Partner

Partenaires

Kontakt

Contact

Shop

Schweizer Recht

Ausländisches Recht

Über unseren Shop

Neuerscheinungen

Nouveautés

Sortiment und Funktionen

Assortiment et recherche

Vorankündigungen

À paraître

Nach Rechtsgebiet

Par domaine juridique

Kommentare

Commentaires

Xu K: General Audio Signal Processing
with Deep Learning

General Audio Signal Processing with Deep Learning

"Chapter1-Introduction".- "Chapter2-Traditional Representation of Audio Signals".- "Chapter3-Machine Learning Methods for Audio Signals".- "Chapter4-Semi-Supervised Learning for Audio Signal".- "Chapter5-Self-Supervised Learning for Audio Signal".- "Chapter 6: Active Learning for Audio Signal".- "Chapter 7: Incremental Learning for Audio Signal Processing".- "Chapter 8: Few-Shot Learning for Audio Signal Processing".- "Chapter 9: Data Augmentation for Audio Signal".- "Chapter 10: Audio Classification".- "Chapter 11: Sound Source Localization".- "Chapter 12: Anomalous Sound Detection".- "Chapter 13: Audio Source Separation".- "Chapter 14: Audio Generation".- "Chapter 15: Audio-language Learning".- "Chapter 16: Audio-visual Signal Analysis".- "Chapter 17: Audio super-resolution".- "Chapter 18: EEG Auditory Decoding".- "Chapter 19: Audio Denosing".- "Chapter 20: Underwater Acoustics".- "Chapter 21: Urban Sound".- "Chapter 22: Industry Sound".- "Chapter 23: Medical Sound".- "Chapter 24: Bioacoustics".- "Chapter 25: Future Perspective".

Building and Deploying AI Applications at Scale

ML and Generative AI in the Data Lakehouse

Shortest Histories

The Shortest History of AI

The Deep Learning Revolution

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

Dive into SQL Server 2025 and uncover its groundbreaking features—guided by one of its key architects. The 2025 release brings SQL Server firmly into the AI age, and this book ensures that you're ready for the leap, walking you through built-in AI for application development, AI-enhanced data analytics with Microsoft Fabric integration—and much more.
At every step of the way, you’ll gain exclusive insights from author Bob Ward, a Principal Architect for the Microsoft Azure Data team, who has worked on every version of SQL Server since OS/2 1.1. With more than 31 years at Microsoft, Ward brings unparalleled expertise and practical knowledge, leaving you and your database in excellent hands.
Ward covers the fundamentals of setup, upgrades, and configuration, and covers advanced features in security, performance, and high availability. He also highlights what makes this the most significant SQL Server release for developers in a decade: support for JSON, RegEx, REST APIs, and event streaming.
Most critically, Ward explores SQL Server 2025’s advanced, secure, and scalable AI integration. After a practical introduction to AI fundamentals to help you integrate artificial intelligence with your data, you’ll learn how to build AI-powered applications deeply integrated with the SQL engine—and elevate your analytics to the next level.
The AI age is here. Be sure your SQL Server databases are ready.
&nbsp;
What You Will Learn
·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; ·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; ·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; ·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; ·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; ·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; ·&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;Use new query processing capabilities to extend the performance of your application
·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; ·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; ·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; ·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; ·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Leverage new tools such as SQL Server Management 21 and Copilot experiences to assist your SQL Server journey
&nbsp;
Who This Book Is For
The SQL Server community, including DBAs, architects, and developers eager to stay ahead with the latest advancements in SQL Server 2025, and those interested in the intersection of AI and data, particularly how artificial intelligence (AI) can be seamlessly integrated with SQL Server to unlock deeper insights and smarter solutions

The AI-Ready Enterprise Database with Microsoft Fabric Integration

SQL Server 2025 Unveiled

Building a Program for Strategy and Oversight

Practical AI Governance

Transform your data replication strategy into a competitive advantage with Oracle GoldenGate 23ai.
This comprehensive guide delivers the practical knowledge DBAs and architects need to implement, optimize, and scale Oracle GoldenGate 23ai in production environments. Written by Oracle ACE Director Bobby Curtis, it blends deep technical expertise with real-world business insights from hundreds of implementations across manufacturing, financial services, and technology sectors.
Beyond traditional replication, this book explores the groundbreaking capabilities that make GoldenGate 23ai essential for modern AI initiatives. Learn how to implement real-time vector replication for RAG systems, integrate with cloud platforms like GCP and Snowflake, and automate deployments using REST APIs and Python. Each chapter offers proven strategies to deliver measurable ROI while reducing operational risk.
Whether you're upgrading from Classic GoldenGate, deploying your first cloud data pipeline, or building AI-ready data architectures, this book provides the strategic guidance and technical depth to succeed. With Bobby's signature direct approach, you'll avoid common pitfalls and implement best practices that scale with your business.
What You Will Learn
<ul>
<li>Master the microservices architecture and new capabilities of Oracle GoldenGate 23ai</li>
<li>Implement secure, high-performance data replication across Oracle, PostgreSQL, and cloud databases</li>
<li>Configure vector replication for AI and machine learning workloads, including RAG systems</li>
<li>Design and build multi-master replication models with automatic conflict resolution</li>
<li>Automate deployments and management using RESTful APIs and Python</li>
<li>Optimize performance for sub-second replication lag in production environments</li>
<li>Secure your replication environment with enterprise-grade features and compliance</li>
<li>Upgrade from Classic to Microservices architecture with zero downtime</li>
<li>Integrate with cloud platforms including OCI, GCP, AWS, and Azure</li>
<li>Implement real-time data pipelines to BigQuery, Snowflake, and other cloud targets</li>
<li>Navigate Oracle licensing models and optimize costs</li>
</ul>
Who This Book Is For
Database administrators, architects, and IT leaders working with Oracle GoldenGate—whether deploying for the first time, migrating from Classic architecture, or enabling AI-driven replication—will find actionable guidance on implementation, performance tuning, automation, and cloud integration. Covers unidirectional and multi-master replication and is packed with real-world use cases.

Transform your data replication strategy into a competitive advantage with Oracle GoldenGate 23ai.This comprehensive guide delivers the practical knowledge DBAs and architects need to implement, optimize, and scale Oracle GoldenGate 23ai in production environments. Written by Oracle ACE Director Bobby Curtis, it blends deep technical expertise with real-world business insights from hundreds of implementations across manufacturing, financial services, and technology sectors.Beyond traditional replication, this book explores the groundbreaking capabilities that make GoldenGate 23ai essential for modern AI initiatives. Learn how to implement real-time vector replication for RAG systems, integrate with cloud platforms like GCP and Snowflake, and automate deployments using REST APIs and Python. Each chapter offers proven strategies to deliver measurable ROI while reducing operational risk.Whether you're upgrading from Classic GoldenGate, deploying your first cloud data pipeline, or building AI-ready data architectures, this book provides the strategic guidance and technical depth to succeed. With Bobby's signature direct approach, you'll avoid common pitfalls and implement best practices that scale with your business.What You Will Learn<ul><li>Master the microservices architecture and new capabilities of Oracle GoldenGate 23ai</li><li>Implement secure, high-performance data replication across Oracle, PostgreSQL, and cloud databases</li><li>Configure vector replication for AI and machine learning workloads, including RAG systems</li><li>Design and build multi-master replication models with automatic conflict resolution</li><li>Automate deployments and management using RESTful APIs and Python</li><li>Optimize performance for sub-second replication lag in production environments</li><li>Secure your replication environment with enterprise-grade features and compliance</li><li>Upgrade from Classic to Microservices architecture with zero downtime</li><li>Integrate with cloud platforms including OCI, GCP, AWS, and Azure</li><li>Implement real-time data pipelines to BigQuery, Snowflake, and other cloud targets</li><li>Navigate Oracle licensing models and optimize costs</li></ul>Who This Book Is ForDatabase administrators, architects, and IT leaders working with Oracle GoldenGate—whether deploying for the first time, migrating from Classic architecture, or enabling AI-driven replication—will find actionable guidance on implementation, performance tuning, automation, and cloud integration. Covers unidirectional and multi-master replication and is packed with real-world use cases.

Powering the Foundation of Data Integration and AI

Pro Oracle GoldenGate 23ai for the DBA

Advances in Geographic Information Science

This edited volume brings together leading experts and researchers from diverse disciplines to provide insights into how geospatial data and AI technologies can be leveraged to tackle pressing environmental issues, ranging from climate change mitigation to natural resource management. By combining geospatial analysis with AI algorithms such as machine learning and deep learning, the book showcases innovative approaches for monitoring, modelling, and managing environmental systems at various scales.
The chapters in this book bridge the gap between theory and practice,offering practical guidance and real-world case studies to readers interested in harnessing the potential of geospatial and AI technologies for sustainability and resilience initiatives. Through a series of chapters covering topics such as remote sensing, spatial data analysis, environmental modelling, and decision support systems, the book equips readers with the knowledge and tools necessary to address complex environmental challenges in an increasingly interconnected world. The book fills an important &nbsp;gap by providing a timely and authoritative resource that not only explores the theoretical foundations of geospatial and AI applications but also offers practical insights into their implementation and potential impact.
Ultimately this volume seeks to empower readers with the knowledge and tools needed to address environmental challenges effectively and promote sustainable resilience in an ever-changing world. The contents here offer valuable insights and guidance for leveraging the transformative power of geospatial and AI technologies to create a more sustainable future.&nbsp;

Advanced Geospatial Intelligence and AI for Environmental Resilience and Sustainable Development

Integration of Federated Learning and Blockchain for Smart Cities

AI Ethics from Industry to Philosophy to Science Fiction

Computers with Salaries and Cemeteries

A complete guide to deep neural networks – the technology behind AI – covering fundamental and advanced techniques to apply machine learning in real-world scenarios. Deep Learning Crash Course goes beyond the basics of machine learning to delve into modern techniques and applications of great interest right now, and whose popularity will only grow in the future. The book covers topics such as generative models (the technology behind deep fakes), self-supervised learning, attention mechanisms (the tech behind ChatGPT), graph neural networks (the tech behind AlphaFold), and deep reinforcement learning (the tech behind AlphaGo). This book bridges the gap between theory and practice, helping readers gain the confidence to apply deep learning in their work.

A complete guide to deep neural networks – the technology behind AI – covering fundamental and advanced techniques to apply machine learning in real-world scenarios. Deep Learning Crash Course goes beyond the basics of machine learning to delve into modern techniques and applications of great interest right now, and whose popularity will only grow in the future. The book covers topics such as generative models (the technology behind deep fakes), self-supervised learning, attention mechanisms (the tech behind ChatGPT), graph neural networks (the tech behind AlphaFold), and deep reinforcement learning (the tech behind AlphaGo). This book bridges the gap between theory and practice, helping readers gain the confidence to apply deep learning in their work.

Deep Learning Crash Course

Connected Diagnoses: IoT, Healthcare, and Digital Forensics investigates the complex intersection of IoT, healthcare, and digital forensics. This book explores the intricate relationships between these fields, with a focus on cybersecurity, patient data ethics, and challenges in IoT investigations. This book advances knowledge on leveraging IoT securely to enhance patient care and digital forensic analysis, providing significant insights from experts along with practical guidance for those operating at the crossroads of these critical disciplines. The book helps professionals grasp, adapt to, and capitalize on the interconnected nature of emerging technologies to ensure ethics, security, and safety. It is a comprehensive resource that benefits researchers and practitioners seeking to understand the convergence of medical technology, interconnected devices, and digital forensics.

IoT, Healthcare, and Digital Forensics

Connected Diagnoses

General Audio Signal Processing with Deep Learning

Bibliografische Angaben

Inhaltsverzeichnis

Schlagworte

Bibliografische Angaben

Inhaltsverzeichnis

Schlagworte

Weitere Titel zum Thema