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020 _a9798868810015
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024 7 _a10.1007/979-8-8688-1001-5
_2doi
050 4 _aQA76.7-.73
072 7 _aUMX
_2bicssc
072 7 _aCOM051010
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072 7 _aUMX
_2thema
100 1 _aParasuraman, Banu.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_988473
245 1 0 _aMastering Spring AI
_h[electronic resource] :
_bThe Java Developer’s Guide for Large Language Models and Generative AI /
_cby Banu Parasuraman.
250 _a1st ed. 2024.
264 1 _aBerkeley, CA :
_bApress :
_bImprint: Apress,
_c2024.
300 _aXV, 424 p. 50 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _a1: Introduction to Generative AI and Large Language Models (LLMs) -- 2; Exploring Spring.io, Spring Components for Gen AI: The Developer's Backbone -- 3: Spring AI and LLMs -- 4: Spring AI and RAG -- 5: Conversational AI with Spring AI -- 6: Function Calling with Spring AI -- 7: Productionizing Spring AI -- 8: Real-world Case Studies.
520 _aDive into the future of programming with this comprehensive guide for Java developers to integrate large language models (LLMs) and Generative AI using the Spring Framework. This book comes at a revolutionary time when AI technology is transforming how we implement solutions in various fields, including natural language processing, content generation, and predictive analytics. With its widespread use in the Java community, the Spring Framework is a logical choice for this integration. By focusing on integrating LLMs and GenAI with Spring, this book bridges a significant gap between cutting-edge AI technologies and traditional Java development practices. The author uses a hands-on approach, guiding you through practical implementation to effectively show how to apply theory in real-world situations. Basic introductions of topics—Spring AI, Spring Framework, and other related AI technologies—evolve into advanced integrations to ensure that you find valuable insights regardless of your starting level. Additionally, this book dedicates sections to security and ethical considerations, addressing the pressing issues associated with AI. With a look at emerging trends and future developments, this book prepares you for what's next, ensuring that you are not just catching up with the current state of technology but are also ready for future advancements. What You Will Learn • Master the integration of LLMs and GenAI with the Spring Framework • Develop practical skills in developing AI-driven applications using Java • Gain insights into handling data, security, and ethical considerations in AI applications • Apply strategies for optimizing performance and scalability in AI-enabled applications • Prepare for future AI trends and technologies .
650 0 _aProgramming languages (Electronic computers).
_966206
650 0 _aJava (Computer program language).
_966213
650 0 _aArtificial intelligence.
_958441
650 0 _aSoftware engineering.
_933953
650 1 4 _aProgramming Language.
_966208
650 2 4 _aJava.
_94794
650 2 4 _aArtificial Intelligence.
_958441
650 2 4 _aSoftware Engineering.
_933953
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9798868810008
776 0 8 _iPrinted edition:
_z9798868810022
776 0 8 _iPrinted edition:
_z9798868813719
856 4 0 _uhttps://doi.org/10.1007/979-8-8688-1001-5
912 _aZDB-2-CWD
912 _aZDB-2-SXPC
999 _c65443
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