000			02031 a2200265 4500
005			20260127120347.0
008			260124b |||||||| |||| 00| 0 eng d
020			_a9780138261412
082			_a006.3 BAS
100			_aBass, Len
245			_aEngineering AI systems: architecture and DevOps essentials
260			_aNew Jersey: _bAddison-Wesley Professional, _c2025
300			_axx, 299p.: _bill.; pbk: _c23cm.
504			_aInclude Index and References.
520			_aIn today's rapidly evolving world, integrating artificial intelligence (AI) into your systems is no longer optional. Engineering AI Systems: Architecture and DevOps Essentials is a comprehensive guide to mastering the complexities of AI systems engineering. This book combines robust software architecture with cutting-edge DevOps practices to deliver high-quality, reliable, and scalable AI solutions. Experts Len Bass, Qinghua Lu, Ingo Weber, and Liming Zhu demystify the complexities of engineering AI systems, providing practical strategies and tools for seamlessly incorporating AI in your systems. You will gain a comprehensive understanding of the fundamentals of AI and software engineering and how to combine them to create powerful AI systems. Through real-world case studies, the authors illustrate practical applications and successful implementations of AI in small- to medium-sized enterprises across various industries, and offer actionable strategies for designing, building, and operating AI systems that deliver real business value. https://www.pearson.com/en-us/subject-catalog/p/engineering-ai-systems-devops-and-architecture-approaches/P200000011757/9780138261450?srsltid=AfmBOoopKOlOwRWBh0qvBny2_-Umrrtpi1loZmIhgURxT2gdGSaR_jEy
650			_aArtificial Intelligence
650			_aSoftware Engineering
650			_aAI Model Life Cycle
650			_aSoftware Architecture
650			_aEngineering and Operating AI Systems
700			_a Lu, Qinghua
700			_aWeber, Ingo
700			_aZhu, Liming
942			_cTD _2ddc
999			_c63897 _d63897