Scalable AI and Design Patterns
Design, Develop, and Deploy Scalable AI Solutions
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Beschreibung
Understand and apply the design patterns outlined in this book to design, develop, and deploy scalable AI solutions that meet your organization's needs and drive innovation in the era of intelligent automation.
This book begins with an overview of scalable AI systems and the importance of design patterns in creating robust intelligent solutions. It covers fundamental concepts and techniques for achieving scalability in AI systems, including data engineering practices and strategies. The book also addresses scalable algorithms, models, infrastructure, and architecture considerations. Additionally, it discusses deployment, productionization, real-time and streaming data, edge computing, governance, and ethics in scalable AI. Real-world case studies and best practices are presented, along with insights into future trends and emerging technologies.
The book focuses on scalable AI and design patterns, providing an understanding of the challenges involved in developing AI systems that can handle large amounts of data, complex algorithms, and real-time processing. By exploring scalability, you will be empowered to design and implement AI solutions that can adapt to changing data requirements.
What You Will Learn
- Develop scalable AI systems that can handle large volumes of data, complex algorithms, and real-time processing
- Know the significance of design patterns in creating robust intelligent solutions
- Understand scalable algorithms and models to handle extensive data and computing requirements and build scalable AI systems
- Be aware of the ethical implications of scalable AI systems
Understand and apply the design patterns outlined in this book to design, develop, and deploy scalable AI solutions that meet your organization's needs and drive innovation in the era of intelligent automation.
This book begins with an overview of scalable AI systems and the importance of design patterns in creating robust intelligent solutions. It covers fundamental concepts and techniques for achieving scalability in AI systems, including data engineering practices and strategies. The book also addresses scalable algorithms, models, infrastructure, and architecture considerations. Additionally, it discusses deployment, productionization, real-time and streaming data, edge computing, governance, and ethics in scalable AI. Real-world case studies and best practices are presented, along with insights into future trends and emerging technologies.
The book focuses on scalable AI and design patterns, providing an understanding of the challenges involved in developing AI systems that can handle large amounts of data, complex algorithms, and real-time processing. By exploring scalability, you will be empowered to design and implement AI solutions that can adapt to changing data requirements.
What You Will Learn
- Develop scalable AI systems that can handle large volumes of data, complex algorithms, and real-time processing
- Know the significance of design patterns in creating robust intelligent solutions
- Understand scalable algorithms and models to handle extensive data and computing requirements and build scalable AI systems
- Be aware of the ethical implications of scalable AI systems
Who This Book Is For
AI practitioners, data scientists, and software engineers with intermediate-level AI knowledge and experience
Explains scalable AI and design patterns, including the challenges of handling large data sets, and real-time processing Provides insights into scalable algorithms, models, infrastructure, and architecture considerations Explores the potential of edge computing for AI scalability
Autor*in
Abhishek Mishra
Themen in »Scalable AI and Design Patterns«
Scalable AI Design patterns Robust intelligent systems AI architecture design Large-scale data processing Real-time AI systems Edge Computing
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“Scalable AI and design patterns is a valuable resource for software architects, developers, and data scientists who are working on creating scalable artificial intelligence (AI) systems. … The book offers practical examples and real-world case studies to help readers apply these patterns to their own AI projects. While the book is geared toward practitioners with a solid foundation in AI and cloud technologies, it provides an excellent roadmap for anyone looking to build robust, scalable AI systems.” (Wael Badawy, Computing Reviews, November 22, 2024)
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