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Zellweger K: Das iPhoto 6 Kochbuch

Das iPhoto 6 Kochbuch

Electric Circuit and Network Analysis

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.

Powering the Foundation of Data Integration and AI

Pro Oracle GoldenGate 23ai for the DBA

Synthesis Lectures on Information Concepts, Retrieval, and Services

This book investigates how academic and public libraries support entrepreneurs by offering diverse business support services in collaboration with other business support actors. The chapters explore opportunities to innovate these services through artificial intelligence (AI) integration and structured experimentation, with a strong emphasis on co-creation between librarians and entrepreneurs. Collaborative AI experimentations are examined as mechanisms to strengthen adoption factors for Generative AI tools and to support informed decisions regarding adoption or switching to the alternative solutions. Two practical experimentation approaches are introduced: Need-Based Experimentation (NBE), addressing service gaps or operational goals; and Curiosity-Based Experimentation (CBE), encouraging exploratory trials of emerging AI tools. Real-world cases from diverse libraries illustrate adaptable, practice-based examples for providing business support services, conducting AI experimentations, and integrating Monitoring &amp; Evaluation (M&amp;E) for both formative and summative assessments. To operationalize these insights, the book includes AI experimentation policies, structured reporting templates, business case formats, and instructional guides for AI tools such as ASReview, Connected Papers, and Citation Gecko. The book advocates that innovation in libraries is achievable for any institution, regardless of size or resources, through experimentation, patrons engagement in AI experimentations, and embedded M&amp;E practices, positioning libraries as active collaborators within their local innovation ecosystems.
&nbsp;In addition, this book:

Bridges theory and practice via consulting-led experiences from academic and public libraries supporting entrepreneurs
Empowers librarians to conduct ethical AI experimentations by combining co-creation with monitoring and evaluation
Translates research into practical insights for library managers to innovate business and traditional services

Support, AI Experimentation, Practical Technologies, Monitoring, and Evaluation

Libraries as Hubs for Entrepreneurship

Concepts, Principles and Applications

Intelligent Computing

Studies in National Governance and Emerging Technologies

This book examines how artificial intelligence systems and their applications in security and defence are entangled with governance and policy processes in the EU. Combining concepts and insights from (critical) security studies and science and technology studies, it argues that behind the various AI-related policy initiatives in the EU are particular narratives on security and defence based on European fears of technological innovation and strategic gaps. In this respect, the book casts light on how such beliefs have become increasingly instrumentalized in the European governance dynamics, and subsequently embedded in successive policy initiatives and security and defence research programmes. It challenges conventional understandings of AI technologies as mere security and defence-enabling instruments, by providing a conceptually driven analysis of how certain visions of AI help govern and control one of the most dynamic emergent socio-technical fields. The book will appeal to all those interested in artificial intelligence, security studies, technology and European governance.&nbsp; Raluca Csernatoni is a Research Fellow at Carnegie Europe, where she works on the nexus between European defence and emerging technologies. She is also Guest Professor at the Centre for Security, Diplomacy and Strategy (CSDS), Vrije Universiteit Brussel, Belgium, and Visiting Faculty in the Department of International Relations, Central European University, Austria.

Artificial Security and the Politics of Hype in the EU

Leben und Arbeiten mit künstlicher Intelligenz. Das Handbuch, um KI erfolgreich anzuwenden

Co-Intelligenz

Ctrl+ Reality – Digitale Kompetenzen für die Schule / für die Sekundarstufe II

Schulbuch SII

Ctrl+ Reality – Digitale Kompetenzen für die Schule

Get an in-depth introduction to the Go programming language and its associated standard runtime libraries. This book is tailored for Java programmers to utilize their existing knowledge to learn Go. You will get a deep understanding of the Go language and obtain a good introduction to the extensive Go standard libraries.The Second Edition is updated for new and enhanced APIs in both Java and Go, including revised discussions on modules and Go generics. Through clear descriptions of Go features, contrasted with similar Java features and new extensive code examples, you will possess enough knowledge of Go's libraries to begin doing effective programming in the language.Go for Java Programmers is structured more like a tutorial than a reference document. It covers key features of Go, but not every little detail as a reference might. Its goal is to get you competent enough in Go and its runtime that you can begin to effectively write Go programs.&nbsp;What You:&nbsp;<ul><li>Examine the key Go Runtime libraries and how they compare to Java libraries.</li><li>See when it is appropriate to use the Go language instead of the Java language.</li><li>Read and understand programs written in Go.</li><li>Write many programs in Go.</li><li>Determine when Go is an appropriate language to develop applications in.</li><li>Discover how the Go and Java languages and development experience compare and contrast.</li></ul>

Learn Google's Go Programming Language

Go for Java Programmers

Es gibt sicher wenige junge Wissenschaftsdisziplinen, die so interdisziplinär angelegt sind wie die Informatik. Aber dennoch scheint die Informatik bereits jetzt schon in die Jahre gekommen zu sein. Die aktuelle Digitalisierung ist in die Arbeits- und Lebenswelt gekommen, nicht nur um zu bleiben, sondern um diese Welt nachhaltig zu verändern. Die Kognitive Kybernetik, die Künstliche Intelligenz, Data Science und dort vor allem die Anwendungsgebiete des Cognitive Computing, insgesamt also die Ausprägung einer zukünftigen Informatik gilt es daher nicht nur in der Forschung und Lehre theoretisch zu besetzen, sondern als ausgestaltete Technologie in der Wirtschaft mehrwertig und nachhaltig als Angewandte Informatik zu etablieren. Flankierend dazu ist zu berücksichtigen, dass die Geschwindigkeit dieser technologischen Entwicklungen sich heute schon spürbar auf das Leben, Arbeiten, das Zusammenleben in der Gesellschaft und damit insgesamt auf die Lebenswelt auswirken, wenngleich die Implikationen dieser Ein- und Auswirkungen noch nicht so klar erkenn- bzw. prognostizierbar erscheinen.&nbsp; Neben einem interdisziplinären Zugang muss es einer zukünftigen Informatik daher gelingen, einen engen Schulterschluss mit den traditionellen Wissenschaftsdisziplinen herzustellen. Insofern versteht der Autor aufgrund seiner Erfahrungen in der Wirtschaft, Forschung und Lehre die „KI“ als Akronym für den derzeitigen Hype der „Künstlichen Intelligenz“, als Abkürzung für die noch von Menschen bestimmte Entwicklung einer „Konstruierten Intelligenz“ und vor allem als Provokation und Ausblick auf die „Künftige Informatik“. Insbesondere die Kognitive Kybernetik und dort die Künstliche Intelligenz werden nach Einschätzung des Autors die Informatik im Allgemeinen und dort deren Teildisziplinen im Speziellen nicht nur verändern, sondern deren künftige Entwicklung insgesamt eventuell sogar dominieren. Der Autor Professor Dr. Matthias Haun ist für die Entwicklung und weltweite Einführung „Kognitiver Lösungen“ verantwortlich. Ziel ist es, durch die Entwicklung solcher intelligenten, lernenden und vorausschauenden Systeme die Digitalisierung und Kognitivierung von Lebenswelten verantwortungsbewusst voranzutreiben, um damit auch deren Einsatz im Sinne der Nachhaltigkeit sicherstellen zu können. Herr Haun leitet zudem zwei interdisziplinäre Forschungsprogramme, in deren Rahmen unter anderem zukünftige Paradigmen, Methoden und Techniken des Cognitive Computing entwickelt werden. Er hat weltweit mehrere Professuren inne, unter anderem seit Januar 2018 eine Shared Professorship für Kognitive Kybernetik und Philosophie der Kognitionswissenschaften. Neben den Forschungen im Bereich der technologisierten Kognitionswissenschaften widmet sich der Informatiker und Philosoph auch um die Transformation dieser Technologien in die Lebenspraxis und positioniert sich kritisch zu den gesellschaftlichen Implikationen. Er bringt 30 Jahre Erfahrung in der Entwicklung intelligenter Lösungssysteme im Finanzdienstleistungssektor, in der Forschung und Industrie mit.

Technologischer Um- und Ausbau der traditionellen Informatik als logische und praktische Konsequenz der Digitalisierung und Kognitivierung zukünftiger Lebenswelten

Künftige Informatik

This book introduces the reader into the field of automata theory and logic. It studies fundamental properties like complementation and determinisation of automata on infinite words and trees, and presents their applications for logics used in program verification. The presentation of such concepts – some of which are 50 years old or more – is given in a modern style and is accompanied by many exercises. The book can be used for self-study or as a basis for a graduate course on automata and logic, presupposing knowledge on finite automata and regular languages of finite words only.

Automata Theory and Logic

Advanced Biotechnology

Enables researchers and engineers to gain insights into the capabilities of machine learning approaches to power applications in their fields Machine Learning and Big Data-enabled Biotechnology discusses how machine learning and big data can be used in biotechnology for a wide breadth of topics, providing tools essential to support efforts in process control, reactor performance evaluation, and research target identification. Topics explored in Machine Learning and Big Data-enabled Biotechnology include: <ul> <li>Deep learning approaches for synthetic biology part design and automated approaches for GSM development from DNA sequences</li> <li>De novo protein structure and design tools, pathway discovery and retrobiosynthesis, enzyme functional classifications, and proteomics machine learning approaches</li> <li>Metabolomics big data approaches, metabolic production, strain engineering, flux design, and use of generative AI and natural language processing for cell models</li> <li>Automated function and learning in biofoundries and strain designs</li> <li>Machine learning predictions of phenotype and bioreactor performance</li> </ul> Machine Learning and Big Data-enabled Biotechnology earns a well-deserved spot on the bookshelves of reaction, process, catalytic, and environmental engineers seeking to explore the vast opportunities presented by rapidly developing technologies.

Machine Learning and Big Data-enabled Biotechnology

... für Dummies

Kreativität in IT und Technik für Dummies

Das iPhoto 6 Kochbuch

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