03641nam a22004215i 4500001001800000003000900018005001700027007001500044008004100059020001800100024003500118050001300153050001400166072001600180072002300196072001500219100007900234245013500313250001800448264005400466300004400520336002600564337002600590338003600616347002400652505061100676520160801287650002902895650004002924650002902964650001202993710003403005773002603039776003603065776003603101776003603137856004603173979-8-8688-0158-7DE-He21320251030111715.0cr nn 008mamaa240311s2024    xxu|    s    |||| 0|eng d  a97988688015877 a10.1007/979-8-8688-0158-72doi 4aQ334-342 4aTA347.A78 7aUYQ2bicssc 7aCOM0040002bisacsh 7aUYQ2thema1 aMishra, Abhishek.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut10aScalable AI and Design Patternsh[electronic resource] :bDesign, Develop, and Deploy Scalable AI Solutions /cby Abhishek Mishra.  a1st ed. 2024. 1aBerkeley, CA :bApress :bImprint: Apress,c2024.  aXVII, 256 p. 7 illus.bonline resource.  atextbtxt2rdacontent  acomputerbc2rdamedia  aonline resourcebcr2rdacarrier  atext filebPDF2rda0 aChapter 1: Introduction to Scalable AI Systems -- Chapter 2: Fundamentals of Scalability in AI -- Chapter 3: Data Engineering for Scalable AI -- Chapter 4: Scalable AI Algorithms and Models -- Chapter 5: Scalable AI Infrastructure and Architecture -- Chapter 6: Scalable AI Deployment and Productionization -- Chapter 7: Scalable AI for Real-time and Streaming Data -- Chapter 8: Scalable AI for Edge Computing -- Chapter 9: Scalable AI Governance and Ethics -- Chapter 10: Case Studies and Best Practices -- Chapter 11: Future Trends and Emerging Technologies -- Chapter 12: Conclusion and Final Thoughts.  aUnderstand 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. 0aArtificial intelligence. 0aPython (Computer program language).14aArtificial Intelligence.24aPython.2 aSpringerLink (Online service)0 tSpringer Nature eBook08iPrinted edition:z979886880157008iPrinted edition:z979886880159408iPrinted edition:z979886880734340uhttps://doi.org/10.1007/979-8-8688-0158-7